Genetic Network and Breeding Patterns of a Sicklefin
Lemon Shark (Negaprion acutidens) Population in the
Society Islands, French Polynesia
, Nicolas Buray
, Jennifer K. Schultz
, Eric Clua
, Serge Planes
1 LabEx «CORAIL» - USR 3278 CNRS-EPHE, Centre de Recherche Insulaire et Observatoire de l’Environnement (CRIOBE), Papetoai, Moorea, French
Polynesia, 2 National Marine Fisheries Service, Silver Spring, Maryland, United States of America, 3 Délégation Régionale à la Recherche et Technologie,
Haut-commissariat de la République française, Papeete, Tahiti, Polynésie Française, 4 Ministère de l’Agriculture et de la Pêche, Paris, France
Human pressures have put many top predator populations at risk of extinction. Recent years have seen alarming
declines in sharks worldwide, while their resilience remains poorly understood. Studying the ecology of small
populations of marine predators is a priority to better understand their ability to withstand anthropogenic and
environmental stressors. In the present study, we monitored a naturally small island population of 40 adult sicklefin
lemon sharks in Moorea, French Polynesia over 5 years. We reconstructed the genetic relationships among
individuals and determined the population’s mating system. The genetic network illustrates that all individuals, except
one, are interconnected at least through one first order genetic relationship. While this species developed a clear
inbreeding avoidance strategy involving dispersal and migration, the small population size, low number of breeders,
and the fragmented environment characterizing these tropical islands, limits its complete effectiveness.
Citation: Mourier J, Buray N, Schultz JK, Clua E, Planes S (2013) Genetic Network and Breeding Patterns of a Sicklefin Lemon Shark (Negaprion
acutidens) Population in the Society Islands, French Polynesia. PLoS ONE 8(8): e73899. doi:10.1371/journal.pone.0073899
Editor: Gabriele Sorci, CNRS, Université de Bourgogne, France
Received April 10, 2013; Accepted July 23, 2013; Published August 13, 2013
Copyright: © 2013 Mourier et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This study benefited from the financial support of the Direction à l’Environnement (DIREN) of French Polynesia and the scientific support of
Coordination Unit of the Coral Reef Initiatives for the Pacific (CRISP Programme), based in New Caledonia. The funders had no role in study design, data
collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
Human population growth has fragmented the range of many
species , leading to significant declines in abundance, loss of
genetic diversity and an elevated risk of extinction [2,3]. Such
patterns are mainly reported from terrestrial systems , but
marine systems are now showing similar trends . Isolation
and reduction in population size erode evolutionary potential
and raise the risk of extinction through inbreeding depression,
leading to the loss of genetic variation or the accumulation of
deleterious alleles [3,6]. To this end, many species have
developed inbreeding avoidance strategies , although some
animal populations naturally show low genetic variability [8,9].
Globally, sharks are threatened by overfishing [10–12]. While
these threats are evident for pelagic species  as by-catch of
commercial fisheries, populations of reef-associated species
are also declining [11,14]. Sharks appear to be particularly
vulnerable to over-exploitation because of their K-selected life-
history strategy (i.e., slow growth, late sexual maturity, long life
spans and low fecundity). As a result, overfished populations
may require several decades to recover [10,11,15]. Chronic
overfishing of sharks has diminished population sizes,
fragmented large populations into small, locally-isolated ones
, and led to trophic cascades . Despite these rapid
declines, little is known about their ability to persist in smaller,
more fragmented populations and to recover from human-
induced bottlenecks . In addition, there is a lack of
information about the fine-scale population genetic structure
and breeding patterns of most reef shark species (but see
18–21). As top predators, sharks frequently exhibit small
population sizes and are therefore a good model to investigate
the interactions between demographic parameters, genetic
population structure, mating system and levels of inbreeding in
natural small marine populations, especially in isolated insular
For 5 years, we monitored a small sicklefin lemon shark
(Negaprion acutidens) population around Moorea, French
Polynesia . This species is a large (≤ 340 cm total length)
coastal shark that occurs in the Indo-Pacific region . The
species is now listed as globally vulnerable on the IUCN
Redlist. It is a viviparous shark giving birth every second year
on average, between August and October, to 1-13 well-
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developed pups after a 10-11 month gestation period . The
small population of Moorea  has not experienced a high
level of exploitation, as sharks are not of commercial interest or
traditionally fished locally, and sharks in French Polynesia have
been formally protected by law since 2006. Low densities may
therefore be a result of natural ecosystem equilibrium in an
isolated, fragmented, insular system and/or due to some recent
natural bottleneck . Meanwhile this species supports part of
the diving industry in French Polynesia with special feeding
dives organised [22,25].
The aim of this study was to describe genetic relatedness
and assign parentage based on microsatellite DNA markers in
order to investigate the genetic makeup and mating output
within a small isolated shark population. Previous parentage
analyses of sharks were mostly based on the reconstruction of
parental genotypes from sampled offspring and, when possible,
included few opportunistic sampled adults in the analysis
[18–20]. The present approach differs since it combines a 5-
years monitoring of the population in Moorea together with a
genetic analysis of relationships among individuals within and
All necessary permits were obtained for the described field
study from the French Polynesia Ministry of Research to the
authors. No specific permission was required for underwater
surveys as they were conducted at a commercial diving site
and only involved photo-identification surveys (see below).
Every shark species is protected under French Polynesian
laws, however, DNA samples were taken by non-invasive
methods approved and conducted under the French Polynesia
Ministry of Research permitting authority (Permit #
653/MRM/SPE/DEV), and no lethal sampling was conducted.
Juvenile sharks were captured with gillnets and released in the
water alive under good conditions and adults were remotely
sampled with a modified speargun with a biopsy tip.
Study background and tissue collection
Our study was conducted in French Polynesia, a fragmented
system of small islands and atolls separated by deep ocean
(depth ≥ 2 000 m), which is expected to increase the effective
isolation of reef-associated populations . We monitored a
population of sicklefin lemon sharks (Negaprion acutidens)
visiting a recreational diving site during a 5-year period in
Moorea (17° S, 149° W; Figure S1). Diving surveys were
implemented on a daily basis representing 1058 days between
January 2005 and September 2009 . Based on photo-
identification , we consistently identified 40 mature sharks
(18 males and 22 females ranging from 2.4 to 3.1 meters total
length), with an average of 26.75 ± 3.33 individuals sighted per
year (24 in 2005, 28 in 2006, 31 in 2007, 29 in 2008 and 24 in
2009). When possible, a fin clip was removed from the dorsal
fin of each new shark using a modified spear gun. As a result,
29 out of 40 individuals (72.5%) were sampled. All 11 non-
sampled sharks were observed only once or very few times
and disappeared before sampling. Additionally, 4 resident
females were sampled in Bora Bora (230 km from Moorea)
where only 12 females (but no males) have been observed.
From this survey, all sharks were classified into behavioural
groups based on the affinity between sharks and their fidelity to
the site  and were assigned to three categories:
• Resident sharks of Moorea: composed of 7 males (M03,
M04, M05, M07, M10, M18 and M31) and 7 females (F08, F11,
F15, F20, F23, F25 and F29);
• Non-resident sharks visiting Moorea occasionally:
composed of 6 males (M09, M12, M19, M34, M36 and M38)
and 9 females (F01, F02, F06, F13, F17, F21, F26, F27 and
• Bora-Bora resident sharks: composed of 4 females only
sighted in Bora Bora (B1, B2, B3 and B4).
In addition to adults on Moorea and Bora-Bora sites we also
captured 52 newborn and immature sharks from different
cohorts between 2006 and 2009 in Moorea and three
neighbouring islands: Tetiaora (40 km), Tahaa (200 km) and
Rangiroa (330 km) (Figure S1). Annual sampling of juveniles
took place soon after pupping by adult females (between
December and February). Most newborn sharks (or age-0)
could be identified based on the presence of an open (or
recently closed) umbilical scar that closes few months after
birth. The age of sharks without umbilical scars was
determined based on body length, whose distribution is
generally non-overlapping between age-0, age-1 and age-2
(85<age-1<100 cm TL, 100<age-1<115 cm TL and
115<age-1<130 cm TL, respectively, as determined based on
ongoing growth calculations from capture-recapture data). This
was also confirmed with recapture of individuals in two
consecutive years. Sharks that were larger than 130 cm TL
were assigned to an unknown year of birth (‘other’). Tissues
were stored in 95% ethanol.
Underwater observations of reproductive status
During our underwater photo-identification surveys, we
reported the presence of dermal bite wounds and scars on
females’ body as a sign of mating activity [21,28]. Courtship
behaviour with males engaged in close following of females
was also reported with identification of male and female ID
when possible . Finally, the period of parturition was
estimated based on the reappearance of newly slender female
after the pregnant female left the site for several days or weeks
DNA isolation and microsatellite genotyping
Genomic DNA was isolated from each fin-clip using a DNA
Purification Kit (Puregene). We isolated 2 species-specific
polymorphic microsatellite loci from Negaprion acutidens and
selected 14 polymorphic microsatellite loci developed for other
shark species (Table S1). All specimens (n = 85) were
genotyped at all 16 polymorphic microsatellite loci. PCRs were
conducted with forward primers labelled with Beckman Coulter
dyes D2, D3 or D4 (Table S1). Amplified fragments were
separated on a Beckman Coulter CEQ 8000 Genetic Analysis
System, with a 400-bp internal size standard. Genotypes and
allele sizes were scored using Beckman-Coulter CEQ TM 8000
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Genetic Analysis System-associated software. Allelic frequency
and expected heterozygosity under Hardy–Weinberg
equilibrium were calculated for each locus in GENALEX 6 .
The presence of null alleles was investigated using
MICROCHECKER . Tests for Hardy-Weinberg and linkage
disequilibrium were conducted in GENEPOP 3.4  and
significant levels were adjusted with sequential Bonferroni
corrections for multiple tests with P < 0.05. Of the 16
microsatellite loci, three did not satisfy Hardy-Weinberg and
linkage disequilibrium assumptions. To test our photo-
identification technique , GENALEX 6  was used to
detect potential identical genotypes belonging to resampled
individuals. No identical genotype was found confirming the
accuracy of our photo-identification technique.
Relatedness and genetic network construction
Maximum likelihood estimates of pairwise relatedness
coefficients and genealogical relationships were calculated with
the software ML-RELATE  computing 5000 iterations. The
program calculates the maximum likelihood relationship
between individual pairs. It determines which of parent-
offspring (PO), full-sibling (FS), half sibling (HS) and unrelated
(U) categories yields the greatest likelihood.
Instead of trying to reconstruct an exact pedigree that is
challenging from genetic data alone in wild populations, we
built a genetic network using relatedness information .
Network analysis is now a common tool used to characterize
animal social associations  including sharks . However,
it has rarely been used to illustrate the genetic relationships
between individuals in a population despite its advantage to
incorporate a large amount of data into a simple visual graph
. The genetic network was built from the matrix of genetic
relatedness together with individual characteristics (size, sex
and group membership) using the programs SOCPROG 
and NETDRAW 2.123 . Only the R values of first-order
genetic relationships (PO, FS and HS) inferred from ML-
RELATE were retained in this network for an easier
The program CERVUS  was first used to find highly
probable mother–offspring and father–offspring pairs.
Assignment to these potential parents was done under a strict
confidence level of 95%. These mother–offspring and father–
offspring pairs were then identified in the input file of COLONY
188.8.131.52  as known maternity and paternity. COLONY 184.108.40.206
 implements a full-likelihood approach to parentage
analysis and was shown to outperform other programs in cases
of less than 20 microsatellite markers . We considered both
parent-offspring relationships and sibship amongst offspring.
Adults were separated by sex, and we assumed a polygamous
mating system for both sexes, therefore allowing the
assignment of half-siblings. We carried out a long-run with
medium likelihood precision and a genotyping error rate of 1%.
The prior probability that the true parent was present in the
sample was set to 0.5 for fathers and 0.25 for mothers based
on the proportion of sampled males and females that were
assigned to offspring by CERVUS. We conducted other runs
varying the input parameters such as the mating system for
each sex. For each analysis, 3 replicate runs were conducted
on the same data set. Each of the replicate runs used different
random number seeds to initiate the simulated annealing
processes. Parental genotype reconstruction was also
performed with COLONY allowing to infer the number of
breeders in the population. Therefore, total number of breeders
was assessed either by reconstructing males and females’
genotypes from young of the year half-sib groups or by directly
assigning parentage to offspring from sampled adults.
To test for inbreeding, we used a Monte Carlo simulation
implemented in STORM 1.0 . This analysis generates
offspring internal relatedness (IR) values expected from the
gene pool if mating is random with respect to parental
relatedness. We calculated the average observed IR for all
offspring (n = 52) and adults (n = 33) sampled. We generated
simulated IR measures by sampling random males (n = 13)
and females (n = 20) with replacement. Each random mating
pair produces a simulated offspring whose internal relatedness
can be measured. The observed mean IR was then compared
with the distribution of average simulated IR produced from
1000 iterations. Potential bias of allelic diversity into IR
estimates was tested by resampling and recalculating IR
values on loci with 5 or more alleles.
Microsatellite summary statistics
Across all individuals of Negaprion acutidens collected for
this work, polymorphism varied from 2 to 15 alleles per locus.
Observed heterozygosity ranged from 0.365 to 0.871 per locus
and expected heterozygosity from 0.395 to 0.871 (Table S1).
Null alleles were detected at loci LS15 and Cli107, as
suggested by the general excess of homozygotes using
MICRO-CHECKER. Overall, significant heterozygote
deficiencies were found in three loci (LS15, Cli107 and Cpl169;
with all P < 0.05 following Bonferroni standard correction). We
therefore decided to remove both LS15 and Cli107 from
subsequent analyses due to evidence of null alleles. Once
analyzing together the remaining 14 loci, no significant
heterozygote deficiencies were observed in the global
Adult population genetic structure
As expected in a wild population, the mean coefficient of
relatedness was low among adults, both within the overall
population of Moorea (mean R ± SD = 0.086 ± 0.137) and
when we included individuals from Bora Bora (mean R ± SD =
0.076 ± 0.128; Table S2). However, the genetic network
illustrates that all individuals are interconnected at least by one
first order genetic relationship except for female B4 from Bora
Bora that is isolated from the network (Figure 1). First order
genetic relationships (PO, FS and HS) accounted for 21.6% of
all pairwise relationships in Moorea and 17.6% when
individuals from Bora Bora are included (Figure 1). The number
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of connections a focal individual has in the network (genetic
degree) ranged from 0 to 11 among the 32 other members of
the network (mean ± SD = 5.6 ± 2.6; Figure 1C), indicating that
individuals have a high number of close relatives in the
population. Residency groups as well as sex categories were
also all genetically linked (Figure 1B). Within-group average
genetic relatedness was significantly different from between
group (P < 0.001) even when excluding resident sharks of Bora
Bora (P < 0.05; Table S2). There was no difference between
sex (P > 0.05; Table S2).
Visual information on reproductive status
Pre-copulatory and courtship behavior, characterized by a
male showing a close nose to tail behavior while following a
female (Figure 2F; Table S3; Video S1), started in August and
lasted until early November (first observation in August 20
last observation in November 1
), with a stable calendar each
Figure 1. Genetic network of the sicklefin lemon shark population from Moorea and Bora Bora. (A) Map of the study
location. (B) The genetic network of adult lemon sharks. Each individual is indicated by a node labelled by shark ID. Circles and
squares indicate females and males respectively and symbol size is indicative of the body length of the shark. Node colour
corresponds to the three defined residency groups. Dyads sharing a first-order genetic relationship are connected by a line, with line
thickness indicating the strength of the genetic relationship (proportional to R values). A ‘spring embedding’ algorithm with node
repulsion for laying out the nodes’ positions  was used to cluster densely connected nodes together with less connected nodes
placed around the edge. (C) Genetic degree (number of first-order genetic relationships an individual has) distribution within the
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year. Several males can be involved in courtship behavior at
the same time following the same female (Figure 2F; Table
S3). Females with specific mating scars were then observed
from the end of September throughout November (Figure 2C;
Table S4). Pregnancy in females became visually apparent in
February and progressed until being fully apparent in May
(Figure 2). Most females followed a 2 years reproductive cycle
(Figure 2A–D) with the exception of females F01 (Figure 2E)
and F21 that became pregnant on 2 consecutive years (Table
S4). Considering the reappearance at the site of newly slender
females together with first newborn sharks found in their
nursery in October, we determined that parturition occurs
between July and November (Figure 2E-F; Table S4).
Therefore, gestation is estimated to last 10 to 11 months.
Parentage analysis assigned 35 of the 52 genotyped
juveniles to at least one parent or a parent pair among the 33
sampled adults (Figure 3). In all case, the three runs gave
consistent results and mating system parameters did not
Figure 2. Inference of reproductive cycle from underwater surveys. (A–D) A two-year reproductive cycle as displayed by
female F11 which was pregnant in 2007 (A), then entered in a resting period (B) and mated in 2008 as shown by dermal bite
wounds on its flanks (C), and was pregnant again in 2009 (D). (E–F) Female F01 is pregnant in 2008 (E) and is followed by males
M10 and M31 in a courtship behavior just after parturition in 2008 (F).
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consistently change parentage assignment results. Of the 35
juveniles, 17 (49%) were assigned only to a female, 13 (37%)
only to a male and 5 (14%) to a parent pair. The two mating
pairs of sampled sharks were F11-M09 (Resident/Non-
resident) and F30-M09 (Non-resident/Non-resident). The 52
juveniles were assigned to 29 distinct litters across the years
(Figure 3). From the adult sharks sampled (13 males and 20
females), only 4 females and 8 males were assigned to a
juvenile. However, the genotype of 29 physically unsampled
sharks (12 males and 17 females) was reconstructed by
COLONY and assigned to a juvenile. No juvenile was assigned
to a female from Bora Bora. Therefore, a total of 41 adult
sharks including 20 males (8 sampled and 12 genetically
reconstructed fathers) and 21 females (4 sampled and 17
genetically reconstructed mothers) contributed to the
reproduction for our sampled juveniles (Table 1).
Female reproductive behaviour
Of the 21 females either sampled or genetically
reconstructed (Table 1), 15 gave birth in Moorea and 4 in
Tetiaroa (Figure 3). Six females returned to the same nursery
on multiple years to give birth, of which 4 returned on a two-
years cycle (F11, F30, #1 and #2; Figure 3) and 2 returned in
consecutive years (#3 and #13; Figure 3). Two litters were
made of juveniles sampled in different nurseries (Figure 3).
Seven (78%) of the 9 litters cumulating more than one young
were the result of polyandrous females with females mating
with 2 to 3 males (Figure 3). Most parturition events confirmed
the dermal bite wounds observed underwater (Figure 2) in the
year prior to parturition (Table S4).
Male reproductive behaviour
In our sample, 10 (50%) of the 20 fathers sired more than
one litter (Figure 3). Five males mated with multiple (2,3)
females in a single year (M09 in 2006; M04 and M09 in 2007;
*6 in 2008; *2 and *3 in 2009). Nine males sired a litter in
multiple years. Male M04 was assigned to offspring of two
different litters of female F30 (Figure 3). Male M05 sired 2
different litters in 2 different years (2008 and 2009) although
this shark has not been sighted in Moorea since early 2006.
Genetic diversity and inbreeding
The mean IR value of offspring was not significantly higher
than expected under random mating (Monte Carlo
randomization (x1000): mean IR ± 95% CI = 0.037 ± 0.056 and
mean simulated IR ± 95% CI = 0.009 ± 0.001, P = 0.142). IR
values calculated from loci with over 5 alleles were not different
from those calculated from all loci (mean IR ± 95% CI = 0.023 ±
0.047; P > 0.05) suggesting that our estimation of IR values
were not inflated by the presence of low allelic diversity at
some loci. Observed maximum IR value was 0.504, 13% (7/52)
of all offspring had IR values higher than 0.25 (the value
expected for offspring of half-sibling mating), and 36% (19/52)
had o-IR larger than 0.125 (Figure S2).
There was a significant inverse relationship between body
size (ca. age) and IR (y = -0.0005x+0.0780; R
= 0.0629; P =
0.011). This was confirmed by a significant difference in R
values between maturity status (F
= 3.248, P = 0.043);
offspring IR values being higher than IR of mature sharks (
0.034; Figure 3A; Figure S2). Finally, offspring IR values did
not vary significantly across years (F
= 0.853, P = 0.472;
This study provides a unique case of long term (5 years)
monitoring and genetic survey used to construct the genetic
network and to infer the mating output of an island adult shark
population. This population is also unique since, unlike many
places in the world, it has been preserved from any human
exploitation, implying that low densities observed are normal
for this population. Our results demonstrate that this small
population displays patterns of connectivity throughout the
archipelago and dispersal which are used as a strategy to
avoid mating with closely related partners.
Population genetic structure and dispersal
Although the mean relatedness was low among adults of the
population, all sharks (but 1) were interconnected through
close to moderate genetic relationships. First order genetic
relationships accounted for 17.6% of all pairwise relationships,
reaching 21.6% when excluding individuals from Bora Bora.
The genetic network (Figure 1) illustrates that sharks from
different residency groups and islands are related, that is likely
a consequence of dispersal . Our results also indicate that
sharks are migrating to breed outside their resident population
(Figure 2). While some individuals of its Atlantic sister species,
Negaprion brevirostris, appear to remain at their natal island,
others disperse before reaching maturity  to colonize other
islands. A similar situation is found in Negaprion acutidens, as
among four resident female sharks of Bora Bora, three (B1, B2
and B3) appeared genetically linked to sharks sighted in
Moorea (resident M03 and M05; non-resident M12 and M34;
Figure 1B). Also, direct migration evidence is available with
some individuals from Moorea being sighted in Tahiti both
within and outside the mating season (i.e. females F15, F20,
F23, F25 and F30; Figure 1A). Moreover, during each breeding
period (September–November), most resident males
disappeared from days to weeks  while non-resident males,
such as male M12, show up in in Moorea, presumably to mate
(Figure 1B). While adult sharks appear to migrate throughout
the archipelago, movement or dispersal in juvenile and
immature sharks may be limited as only two age-0 juveniles
were caught away from their littermates within the same island
(female J4A about 8 km away in Moorea and Tet9 about 1.5
Number of breeders determined by direct
parentage assignment and genotype reconstruction
conducted in program COLONY.
Mothers Fathers Total
Physically sampled 4 8 12
Genetically reconstructed 17 12 29
Total (Ne) 21 20 41
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Figure 3. Female reproduction inferred from parentage assignment. Litters are shown by years for each female with the
assigned father(s) and juvenile(s). Sampled individual adult sharks are indicated in bold. Mothers and fathers inferred through
genotype reconstruction by the program COLONY are identified by #ID and *ID, respectively. Colour of juveniles refers to their
sampling nursery site (Figure S1). Note that juvenile Tet5 was sampled in 2008 in Tetiaroa but was assigned to the birth year 2007
due to its size (110 cm) corresponding to an age-1 juvenile, while subadult Sub1 was sampled in 2008 at the size of 125 cm and
subsequently assigned to year of birth 2006. Finally, Tet1 was assigned to an unknown year as we were not able to determine its
year of birth.
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km away in Tetiaroa). However, female Tet1 (180 cm TL)
caught in Tetiaroa is an offspring of female 1 that gave birth in
Varari (Moorea) in 2007 and in 2009; therefore, this immature
shark can either correspond to a dispersal event from its birth
location or a change in nursery location of its mother (female 1)
for parturition. The paucity of studies on Negaprion acutidens
does not provide further information on the year of first
dispersal (or emigration from nursery) of juveniles, but a recent
study showed that among immature sharks (i.e., 141 < TL <
202 cm) the first sharks to leave the study area was about 150
cm TL . Individual sharks have been shown to emigrate
from their nursery during their third year in the sister species
Negaprion brevirostris  and in their first year in
Carcharhinus melanopterus . However, some species delay
their dispersal until reaching maturity . Therefore, while
sicklefin lemon sharks may start emigration from nurseries
during their first year, dispersal rate in the population may
increase throughout the shark’s growth . Overall, sicklefin
lemon sharks in the Society Islands appear to be structured as
a mixed population of individuals moving throughout the
archipelago (Figure 1; Figure 3).
From parentage analysis, we were able to investigate the
mating system and recruitment patterns of lemon sharks in the
archipelago. Like other reef sharks depending on nurseries for
recruitment [18,20,21], most females showed philopatry to
particular nurseries (Figure 3) although this was not the case
for all of them (Figure 3). Negaprion acutidens shares nursery
locations with Carcharhinus melanopterus in Moorea and
Tetiaroa [21,47]. As females mostly followed a biennial
reproductive pattern, some did not exhibit a two-year cycle
(Figure 2; Figure 3; Table S4). Therefore, females may follow
an average two-year reproductive cycle in this species, but like
female F01, may sometimes be mated to harassing males just
after parturition (Figure 2E-F; Table S3). Of the 20 genetically
sampled females, only 4 used one of our sampled nurseries.
Therefore, the other females either did not reproduce during
the study period or gave birth at different, unsampled nursery
locations (Table S4). Based on our parentage analysis and
genotype reconstruction, a total of 41 adult breeders (20 males
and 21 females; Table 1) were found in our system. Although
this may be an underestimate due to unsampled nursery
locations in our study area, the number of breeders is relatively
low. Most litters (78%) had multiple sires showing the
prevalence of polyandrous female mating as it is commonly
found in reef sharks [19,20]. This proportion may be
underestimated as the monogamous females had small,
potentially incompletely sampled litters. Male reproductive
success was highly skewed with few males siring litters on
multiple occasions within and across years (Figure 3),
potentially due to dominance hierarchy among them or
migratory strategies during the mating season .
The mean offspring internal relatedness (mean IR = 0.03)
was not significantly higher than expected under random
mating. However, maximum offspring IR values (IRmax = 0.50)
were higher than those found in offspring of its sister species
Negaprion brevirostris in the Bahamas (IRmax = 0.05 ). IR
values were lower to that of full-siblings (mean IR = 0.14) in
Squalus acanthias litters , although the estimates were
limited to 7 microsatellite markers. Even the critically
endangered Pristis pectinata did not reveal inbreeding (mean
IR = -0.02 ), perhaps due to the absence of migration
barriers of a continuous coastal environment. The same level
of inbreeding was found in Carcharhinus melanopterus,
another shark species of the Society Islands . Negaprion
acutidens clearly developed some inbreeding avoidance
strategy by conducting specific behaviour including dispersal
and migrations across the archipelago. Polyandry is often
expected to effectively increase the cumulative genetic
variation in a single litter and therefore decrease inbreeding. At
the population level, this effect is likely to be mitigated by an
increased variance in male reproductive success .
Additionally, studies on Negaprion brevirostris [19,48]
suggested that high multiple paternity in lemon sharks is more
likely a result of convenience polyandry than of indirect genetic
benefits such as inbreeding avoidance. Therefore, it remains
unlikely that polyandry alone play a major role in inbreeding
Considering these behaviours and the mating system
displayed by sicklefin lemon sharks to avoid inbreeding, the
observed degree of inbreeding is unusual for mobile free-living
marine species. Chapman et al.  argue that male-biased
dispersal from their natal area as well as no evidence that
certain males dominate paternity may reduce the likelihood of
inbreeding in K-selected elasmobranchs. These life history
characteristics and reproductive behaviour are less evident for
Negaprion acutidens in French Polynesia as: (1) a few males
appear to dominate paternity (Figure 3) (2), some males are
resident to an island and do not roam like other species do
, and (3) although evidence for dispersal was found,
individuals within the entire Archipelago remain closely related
(Figure 1). Another reason that may limit the effectiveness of
inbreeding avoidance may be the fragmented habitat in this
region which tends to isolate populations  and may reduce
the opportunity to find unrelated mates.
In addition, significantly higher IR values in juveniles than in
adults (Figure 4; Figure S2) demonstrate a temporal change in
inbreeding levels. Such a change, that suggests variation in
fitness through time can result either from individuals with
higher IR values progressively migrating away from their natal
site or some differential mortality with individuals with higher IR
values showing lower survival rate than juveniles with higher
genetic diversity. Longer monitoring and redundancy of such
pattern in inbreeding values will be necessary to determine
which hypothesis should be favored.
Individuals from this local population of sickefin lemon sharks
in the Society archipelago share many first-order genetic
relationships providing evidence that population size in this
species is fairly limited in the context of islands at least in
French Polynesia, but likely in isolated islands system of the
Relatedness and Reproduction in a Shark Population
PLOS ONE | www.plosone.org 8 August 2013 | Volume 8 | Issue 8 | e73899
Pacific. This low genetic variability has encouraged sicklefin
lemon sharks to develop different strategies to avoid mating
between close relatives with evidence of migrations across
islands and atolls. The highly isolated and fragmented
environment of French Polynesia  may limit encounter rate
of unrelated mates despite dispersal and migrations across the
Society Islands. These results encourage for long-term
monitoring to survey the population response to increasing
anthropogenic factors  despite the economic importance of
these sharks in the local tourism industry .
Figure 4. Patterns of distribution in internal relatedness
values (IR). (A) IR values across the maturity stage of
individuals (categories: juvenile < 100 cm, immature = 100-199
cm and mature > 200 cm). (B) IR values of newborn sharks
(cohorts) across years. Box plots show the median (line within
the boxes), mean (white diamond) and interquartile ranges IQR
(boxes). Raw data points are indicated by black circles.
Figure S1. Sampled nursery locations. (A) Map of French
Polynesia with sampled islands. (B) Sampled nursery locations
in Tetiaroa. (C) Nursery locations in Moorea. Circles are
coloured according to the nursery location used in the study
and black circles refers to adult sampling sites.
Figure S2. Distribution of internal relatedness values (IR)
of adult (black bars) and juvenile (grey bars) lemon sharks.
Table S1. Description of the 16 microsatellite loci used to
genotype sicklefin lemon sharks. Dyes: fluorescent
Beckman Coulter dyes labels; Ta: annealing temperature (°C);
N: number of individual scored; H
: observed heterozygosity;
: expected heterozygosity; k: number of alleles; Fis:
inbreeding coefficient; H–W: exact test for departure from
Table S2. Distribution of average relatedness values
across categories (sex and socio-residency groups). Mean
relatedness is displayed together with SD in parenthesis.
Table S3. Underwater observations of male courtship
behaviour in sicklefin lemon sharks in Moorea. For each
year, the females that each male was observed to follow is
Table S4. Underwater visual estimations of reproduction
timing in sicklefin lemon sharks in Moorea. DBW: Dermal
Bite Wound (dates of observations are indicated); P: Parturition
indicated in grey (estimated to have occurred during the time
the female was absent from the observation area; dates of
disappearance for pregnant females are indicated when
Video S1. Courtship behavior with female F01 is closely
followed by male M10 in 23 October 2008. Female F01 was
in near to term gestation in August 2008 (Figure 2E) and
presumably gave birth between August and October 2008
(Table S4). This female returned to our study site on 8 October
2008, was seen followed by male M10 in a courtship and then
joined by male M31 (Figure 2F). Note that both male M10 and
female F01 are focused in their courtship behavior and do not
pay attention to the diver.
We would like to thank the private diving company Top Dive in
Moorea for logistic support and René Galzin, Centre de
Relatedness and Reproduction in a Shark Population
PLOS ONE | www.plosone.org 9 August 2013 | Volume 8 | Issue 8 | e73899
Recherche Insulaire et Observatoire de l’Environnement
(CRIOBE), Pablo Saenz-Agudelo, Thomas Vignaud and
Elisabeth Rochel, Centre de Biologie et d’Ecologie Tropicale et
Méditerranéenne (CBETM) for scientific and technical support.
Conceived and designed the experiments: JM NB EC SP.
Performed the experiments: JM NB JKS EC SP. Analyzed the
data: JM SP. Contributed reagents/materials/analysis tools: JM
SP. Wrote the manuscript: JM NB JKS EC SP.
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