Population identification of common cuttlefish ( Sepia officinalis ) inferred from genetic, morphometric and cuttlebone chemistry data in the NE Mediterranean Sea

Abstract

The population structures of the common cuttlefish Sepia officinalis from the north-eastern Mediterranean (Antalya and Iskenderun Bays), Aegean (Izmir Bay) and Marmara Seas were analyzed with mtDNA PCR-RELP. body morphometry and cuttlebone chemistry. Analysis of a ND 5/6 (Nikotin Amid Adenin Dehidrojenaz-5/6) gene segment of mtDNA revealed seven haplotypes from 120 individuals. No haplotype sharing was observed among sampling sites. The average nucleotide divergence between samples was 0.009390. and the highest genetic divergence (0.015279) was observed between the Iskenderun Bay and Marmara Sea samples. The lowest genetic divergence (0.003786) was between the Aegean Sea and Antalya Bay samples. Highly significant differences (P<0.001) between all sampling sites were observed in both the Monte Carlo and AMOVA analyses. In the UPGM tree, the neighbouring Antalya and Aegean samples clustered as the closest chides, and the most isolated Marmara and Iskenderun Bay samples clustered as die most divergent chides. In discriminant function analysis. the classification success rates in assigning fishes to the correct region of origin were 66 and 100% for morphometry and cuttlebone chemistry respectively. In the morphometric analysis, only the Marmara Sea and Iskenderun Bay samples were differentiated from each other, and the rest of the samples overlapped each other. In cuttlebone chemistry analysis, univariate statistics revealed highly significant (P<0.001) differences among locations for 12 elements: Al. Ca. Cd. Cr, Cu, Fe, K, Mg, Mn, Na. Pb, Zn. In multivariate analysis, highly significant differences (P<0.001) were observed between the four locations. This study showed that there are four discrete populations of S. officinalis in Turkish coastal waters.

Full text

Population identification of common cuttlefish (Sepia
officinalis) inferred from genetic, morphometric and
cuttlebone chemistry data in the NE Mediterranean Sea
CEMAL TURAN and DENIZ YAGLIOGLU
Fisheries Genetics Laboratory, Department of Basic Sciences, Faculty of Fisheries, Mustafa Kemal University,
31200 Iskenderun, Hatay, Turkey. E-mail: cturan@ymail.com
SUMMARY: The population structures of the common cuttlefish Sepia officinalis from the north-eastern Mediterranean
(Antalya and Iskenderun Bays), Aegean (Izmir Bay) and Marmara Seas were analyzed with mtDNA PCR-RFLP, body
morphometry and cuttlebone chemistry. Analysis of a ND 5/6 (Nikotin Amid Adenin Dehidrojenaz-5/6) gene segment of
mtDNA revealed seven haplotypes from 120 individuals. No haplotype sharing was observed among sampling sites. The
average nucleotide divergence between samples was 0.009390, and the highest genetic divergence (0.015279) was observed
between the Iskenderun Bay and Marmara Sea samples. The lowest genetic divergence (0.003786) was between the Aegean
Sea and Antalya Bay samples. Highly significant differences (P<0.001) between all sampling sites were observed in both the
Monte Carlo and AMOVA analyses. In the UPGM tree, the neighbouring Antalya and Aegean samples clustered as the clos-
est clades, and the most isolated Marmara and Iskenderun Bay samples clustered as the most divergent clades. In discrimi-
nant function analysis, the classification success rates in assigning fishes to the correct region of origin were 66 and 100% for
morphometry and cuttlebone chemistry respectively. In the morphometric analysis, only the Marmara Sea and Iskenderun
Bay samples were differentiated from each other, and the rest of the samples overlapped each other. In cuttlebone chemistry
analysis, univariate statistics revealed highly significant (P<0.001) differences among locations for 12 elements: Al, Ca, Cd,
Cr, Cu, Fe, K, Mg, Mn, Na, Pb, Zn. In multivariate analysis, highly significant differences (P<0.001) were observed between
the four locations. This study showed that there are four discrete populations of S. officinalis in Turkish coastal waters.
Keywords: Sepia officinalis, population identification, genetic, morphometry, cuttlebone chemistry.
RESUMEN: Identificación poblacional de sepia (Se p i a o f f i c i n a l i S ) en Mediterráneo NE inferido a partir de da-
tos genéticos, morfométricos y químicos del sepión. – La estructura poblacional de la sepia común del Mediterráneo
noreste (bahías de Antalya y de Iskenderun), Mar Egeo (Bahía de Izmir) y Mar de Mármara ha sido analizada mediante
la técnica de PCR-RFLP del ADN mitocondrial (mtDNA), la morfometría del cuerpo y química del sepión. El análisis de
variabilidad de secuencia de un fragmento del gen mitocondrial ND 5/6 (Nikotin Amid Adenin Dehidrojenaz-5/6) de 120
individuos reveló siete haplotipos distintos. Ninguno de ellos compartido entre localidades. La divergencia nucleotídica me-
dia entre muestras es de 0.009390, con el máximo valor de divergencia genética (0.015279) observado entre las localidades
de la bahía Iskenderun y el Mar de Mármara, y el mínimo valor de divergencia genética (0.003786) entre las localidades del
mar Egeo y la bahía de Antalya. Los análisis basados en las simulaciones de Monte Carlo y AMOVA mostraron diferencias
altamente significativas (P<0.001) entre todas las localidades. En el árbol filogenético de UPGMA, las localidades colindan-
tes de Antalya y de Mar Egeo se agrupan en la misma rama. Por otro lado, las localidades más aisladas, Mar de Mármara y
bahía de Iskenderun, se distribuyen en los clados más divergentes. En el análisis de la función discriminante, la clasificación
de las tasas de éxito en la asignación de especímenes a las regiones fue 66% para el análisis morfométrico y un 100% para la
química del sepión. En el análisis morfométrico solamente se detectaron diferencias significativas entre las muestras del Mar
de Mármara y la bahía de Iskenderun, mientras que el resto de localidades se agrupan entre ellas. En el análisis de la química
del sepión, el análisis univariante ha revelado diferencias altamente significativas (P<0.001) entre todas las regiones en 12
elementos Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Pb, Zn. En el análisis multivariante se observan diferencias altamente
significativas (P<0.001) entre las cuatro localidades. Este estudio muestra la presencia de cuatro poblaciones separadas de S.
officinalis a lo largo de las aguas de la costa turca.
Palabras clave: Sepia officinalis, identificación poblacional, genética, morfometría, química del sepión.
Sc i e n t i a Ma r i n a 74(1)
March 2010, 77-86, Barcelona (Spain)
ISSN: 0214-8358
doi: 10.3989/scimar.2010.74n1077

78 • C. TURAN and D. YAGLIOGLU
SCI. MAR., 74(1), March 2010, 77-86. ISSN 0214-8358 doi: 10.3989/scimar.2010.74n1077
INTRODUCTION
Reliable management of fish populations should
be based on truthful biological data for sustain-
able exploitation of biological marine resources
(Carvalho and Hauser, 1994). In marine species,
demographic processes and fishery activities can
vary considerably between populations or stocks.
The potential capacity of populations to adapt and
evolve as independent biological entities in different
environmental conditions depends on the exchange
of individuals between populations. Restricted
exchange may lead to self-recruiting units, which
have divergent genotypes, chemical structures and
morphology (Carvalho and Hauser, 1994; Turan et
al., 2006; Volpedo and Cirelli, 2006). Identification
of intraspecific groups of marine fish species with
different genetic and morphological characteristics
is essential for understanding population dynamics
and estimating sustainable harvests (Carvalho and
Hauser, 1994).
The common cuttlefish (Sepia officinalis L. 1758)
is a demersal and neritic species occurring predomi-
nantly on sandy to muddy bottoms from the coastline
to about 200 m depth (FAO, 2003), and has a high
commercial value in European countries (Perrin et
al., 2004). It is distributed along the NE Atlantic,
from the Baltic Sea to Senegal, and throughout the
Mediterranean, Aegean and Marmara Seas (Guerra,
1992). S. officinalis is the most widely-known spe-
cies of cuttlefish in Turkey. The contribution of S.
officinalis to local fisheries differs in each sea: 9%
of the total fish catch in the Aegean Sea (Salman et
al., 1997) and 5-6% in the Mediterranean Sea (Sal-
man and Katag˘an, 2004). There has been a number
of stock structure analyses of S. officinalis carried
out in European waters which report biology, mor-
phology and genetic differences between popula-
tions (Shaw et al., 1999; Perez-Losada et al., 1999;
Perez-Losada et al., 2002; Wolfram et al., 2006).
However, in Turkish waters there is only informa-
tion on the biology and distribution of S. officinalis
(Duysak et al., 2004; Salman and Katag˘an, 2004).
There is no information on the population structure
of S. officinalis in the fishing grounds of the north-
eastern Mediterranean, Aegean or Marmara Seas.
Studies on mtDNA using restriction fragment
length polymorphism (RFLP) analysis have shown it
to be a powerful genetic marker for assessing genetic
variation among populations (Hauser et al., 2001;
Turan et al., 2009). Maternal inheritance and the
absence of recombination make mitochondrial DNA
an appropriate tool for reconstructing the recent his-
tory of populations (Avise, 1994). Moreover, fish
body morphometry and otolith chemistry have been
commonly used for stock delineation, since variation
in body morphometry and otolith chemistry between
stocks indicates that different stocks have spent sig-
nificant periods of their lives in different environ-
ments (Campana, 1999).
The first objective of the present study was to
investigate the population structure of S. officinalis
throughout the Marmara, Aegean and north-eastern
Mediterranean Seas using PCR–RFLP analysis of
mitochondrial ND 5/6 genes, morphometry and
cuttlebone chemistry. The second objective was to
determine the discriminative potential of cuttlebone
chemistry for identifying populations. This study is
the first to use cuttlebone chemistry to identify cut-
tlefish populations.
MATERIALS AND METHODS
Sampling
Samples were collected separately by commer-
cial fishing vessels (Trawl) from four fishing ports
in the Aegean (Izmir Bay), Marmara (Bandirma
Bay) and north-eastern Mediterranean Seas (An-
talya and Iskenderun Bays) (Fig. 1). Abbreviations
of sampling areas are given in Table 1. Following
capture, the cuttlefish specimens were immediately
transferred to the laboratory. The sample size and
relevant information of collected samples are given
Fig. 1. – Map of the sampling locations for the common cuttlefish.
 indicates sampling location; MS, Marmara Sea; AS, Aegean Sea;
NMS1, north-eastern Mediterranean Sea (Antalya Bay); NMS2,
north-eastern Mediterranean Sea (Iskenderun Bay).

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in Table 1. In the laboratory, morphometric meas-
urements (mm) of the cuttlefish were taken of each
specimen according to Kassahn et al. (2003). After
the morphometric measurements had been taken,
each individual was dissected: the cuttlebone was
removed from the tissues and stored at −30ºC.
Genetic sampling
Total DNA was extracted from the muscle using
the standard phenol: chloroform: isoamyl alcohol
procedure (Sambrook et al., 1989). PCR amplifica-
tion of the mitochondrial ND 5/6 gene was carried
out using the universal primers:
ND5/6-a: 5’-AAC AGT TCA TCC GTT GGT CTT AGG-3’
ND5/6-b: 5’-TAA CAA CGG TGG TTC TTC AAG TCA-3’
The amplification was performed with a profile
of 94
o
C for 4 min, followed by 35 cycles of 94
o
C/30s
strand denaturation, 52ºC/20s annealing and 72
o
C/1
min 30 sec primer extensions, and a final 7 min
elongation at 72ºC. The ND 5/6 rDNA amplification
conditions were: 1.5 µl 10 x polymerase buffer, 0.5
µl dNTP (10 mM), 0.3 µl Taq DNA polymerase (3
U/µl), 0.10 µl primers, 1µl template DNA, and water
for a total reaction volume of 25 µl.
The PCR product was restricted with 6 endo-
nucleases: BsurI (HaeIII), AluI, Bsh1236I (Fnu-
DII), Hin6I (HhaI), RsaI, XhoI. The fragments of
the restricted DNA samples were separated on 6%
polyacrylamide gels, together with a pGem marker
(Promega). A modified silver nitrate staining pro-
tocol (Tegelstrom, 1987) was used to visualize the
DNA fragments.
Nucleotide sequence diversities and divergence
(Nei and Tajima, 1981) were determined using the
REAP computer package (McElroy et al., 1991).
The significance of geographic heterogeneity in
haplotype distribution was tested using a Monte
Carlo simulation (Roff and Bentzen, 1989) with 100
randomizations of the data. A molecular analysis of
variance (AMOVA) using F
ST
was also performed
to detect the level of gene flow between populations
with Arlequin v3 (Excoffier and Schneider, 2005). A
mismatch analysis was performed using Arlequin v3
to compare the occurrence of demographic changes
in the populations (Rogers and Harpending, 1992).
This analysis compares the distribution of the fre-
quency of pairs of individuals who differ by a cer-
tain number of nucleotide differences. The distance
matrices of pairwise comparisons among haplotypes
were used to generate trees with the unweighted
pair-group method with arithmetic averages (UPG-
MA; Sneath and Sokal, 1973) using PHYLIP v 4.
Bootstrapping with replicates encompassing 1000
datasets was performed to investigate the robustness
of nodes in each cluster.
PCR-RFLP generated fragment profiles were
classified by letters which were then combined to
define composite mtDNA haplotype patterns. The
size of the restriction fragments were estimated from
their mobilities relative to a standard DNA ladder
molecular size marker using DNA-FRAG version
3.03.
Morphometric measurements
Morphometric characters on the dorsal view and
tentacular club of S. officinalis were measured with
a digital compass. The abbreviations and name of the
morphometric measurements are: TL total length; ML
mantle length; MW mantle width: NW neck width;
ED eye diameter; CSD club sucker diameter; CL club
length; DBE distance between eyes (Fig. 2).
Significant linear correlations between all mor-
phometric characters and the standard length of
cuttlefish were detected. In order to eliminate any
size effects in the dataset, an allometric formula by
Elliott et al. (1995) and Lleonart et al. (2000) was
applied to remove length effects in the samples. The
efficiency of size adjustment was evaluated by test-
ing the significance of correlations between trans-
formed variables and the length of cuttlefish. All
calculations were performed in SPSS and SYSTAT
software packages.
Table 1. – Sampling details of S. officinalis used in this study. MTL, mean total length (mm). Standard deviations of MTL are given in
brackets. F, female; M, male.
Sampling Area Abbreviation Sampling Area Coordinates Sex (F/M) Sample size MTL Collection date
Marmara Sea MS 400°36’02”N 270°21’41”E 18/12 30 35.32 (4.19) 17.01.2007
Aegean Sea AS 380°49’24”N 260°33’27”E 17/13 30 18.84 (3.99) 08.12.2006
Mediterranean Sea (Antalya Bay) NMS1 360°48’45”N 300°41’11”E 24/6 30 18.62 (4.68) 05.12.2006
Mediterranean Sea (Iskenderun Bay) NMS2 360°34’29”N 350°50’08”E 17/13 30 22.15 (3.24) 12.12.2006

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Cuttlebone chemistry
The cuttlebones from all samples were dried at
65ºC for 5 days to constant weight and then reduced
to powder using a porcelain mortar and pestle. Aliq-
uots (500 mg) of the samples were digested with 4 ml
of 14N Ultra pure HNO
3
and 1 ml of 22N Ultra pure
HClO
4
at 100ºC on a hot plate for 3 days. After evap-
oration of the acids, the residues were resuspended
in 5 ml 0.3 N HNO3. The blank was prepared in the
same way as the samples. Concentrations of Al, Ca,
Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Pb, Zn were ana-
lyzed by solution-based inductively coupled plasma-
atomic emission spectrometry (ICP-AES; Varian®
Liberty Series II, USA). A phosphor (P) standard
was prepared from the Merck® Standards for ICP-
AES. The calibration curve was obtained with at
least 5 to 7 points. The values of the elements and
blank, obtained from the ICP-AES, were calculated
and values expressed as µg.g-1 dry weight.
RESULTS
Genetic results
A total of 7 composite haplotypes was found
from 120 individuals. The composite haplotypes
and their occurrence in each population are given in
Table 2. No haplotype sharing was observed among
populations. The average haplotype and nucle-
otide diversity within populations were 0.1075 and
0.000818 respectively. The average nucleotide di-
versity and nucleotide divergence between samples
were 0.010208 and 0.009390 respectively. The high-
est nucleotide divergence (0.015279) was observed
between the Iskenderun Bay (NMS2) and Marmara
Sea (MS) samples, and the lowest nucleotide diver-
gence (0.003786) was observed between the Aegean
Sea (AS) and Antalya Bay (NMS1) samples.
Tests for genetic heterogeneity in haplotype
frequencies revealed overall highly significant het-
erogeneity (P<0.001) among S. officinalis samples,
which indicates genetic sub-structuring within the
species (Table 3). In pairwise comparisons us-
ing Monte Carlo χ
2
tests significant differences
(P<0.001) in haplotype frequency were observed
between all samples (Table 3). Mantel’s test showed
that the genetic distances between the samples
were significantly associated with their geographi-
cal association (r = 0.78; P<0.05). The AMOVA
test also supported the highly restricted intermin-
gling between the locations, especially between
the Iskenderun Bay (NMS2) and Aegean Sea (AS)
samples (Table 3). The parameters of the model of
sudden expansion and the goodness-of-fit test to the
Fig. 2. – Morphometric characters of S. officinalis measured: a) dorsal view, b) tentacular club, TL total lenght; ML mantle length; MW mantle
width: NW neck width; ED eye diameter; CSD club sucker diameter; CL club length; DBE distance between eyes.

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model in the mismatch analyses are given in Table 4.
All populations were fitted to an expansion model.
Estimated τ values (time in number of generations
after expansion) were 0.077 and 0.334 for NMS1
and MS respectively. Zero τ values were detected
for the other populations, indicating that population
expansion in NMS2 and AS may be due to a recent
bottleneck.
The genetic relationship between samples is sum-
marized in the form of a UPGM dendrogram (Fig.
3). In the first clad, the Antalya Bay (NMS1) and
Aegean Sea samples clustered as the closest clades,
while the Marmara Sea sample was in the neigh-
bouring clad. The Iskenderun Bay sample (NMS2)
clustered as the most divergent (Fig. 3). High boot-
strapping values were detected for each node on the
UPGM dendrogram.
Morphometric results
Univariate statistics (ANOVA) revealed highly
significant (P<0.001) differences among locations
for all 6 morphometric measurements. In DFA, the
first DF accounted for 72% and the second account-
ed for 26% of the between-population variability.
The graphic representation of the first two canoni-
cal axes revealed a clear separation of the Marmara
Sea and Iskenderun Bay samples and overlapping
of the Aegean Sea and Antalya Bay samples (Fig.
4). Mantel’s tests using the Euclidean distance for
morphometric characters (r=0.59; P>0.05) between
these samples were not significantly associated with
geographical distances.
The overall percentage of reclassification by
cross-validation was 66%. The proportion of cor-
rectly classified individuals into their original sample
Table 2. – Frequency of 7 composite mtDNA haplotypes from RFLP data within the studied stocks of S. officinalis. Letters reflect individual
haplotypes for six restriction enzymes; BsurI, AluI, Bsh1236I, Hın6I, RsaI, XhoI (left to right). H, haplotype diversity; N, nucleotide diversity;
S.E., standard error.
Restriction enzymes Sampling sites
Haplotypes BsurI AluI Bsh1236I Hın6I RsaI XhoI NMS1 NMS2 AS MS Total
Type 1 A A B A B A 0 30 0 0 30
Type 2 A B A A A A 28 0 0 0 28
Type 3 A B C B B A 2 0 0 0 2
Type 4 A A A A A A 0 0 30 0 30
Type 5 B A A A C A 0 0 0 25 25
Type 6 B A A A A A 0 0 0 3 3
Type 7 B B B A C A 0 0 0 2 2
Total 30 30 30 30 120
Average
H 0.1287 0.0000 0.0000 0.3011 0.1075
S.E.(+/-) 0.07916 0.0000 0.0000 0.10222 0.00509
N 0.001835 0.0000 0.0000 0.001437 0.000818
Table 3. – Pairwise estimates of nucleotide divergence (below
diagonal) and F
ST
(above diagonal) values among S. officinalis
populations. ***, significance value (P<0.001).
Stock NMS1 NMS2 AS MS
NMS1 - 0.92476*** 1.00000*** 0.96323***
NMS2 0.013443*** - 0.83908*** 0.88231***
AS 0.004704*** 0.008774*** - 0.92687***
MS 0.011728*** 0.015998*** 0.006599***
Table 4. – Parameters of the sudden expansion model and
goodness-of-fit test to the model with respective significance for
each population. S, number of polymorphic sites; θ
0
, preexpansion
population size; θ
1
, postexpansion population size; τ, time in number
of generations; SSD, sum of squared deviations; Hri; Harpening’s
Raggedness index; * Significant at P<0.05.
Population
Parameters NMS1 NMS2 AS MS
S 12 0 0 6
θ
0
0 0 0 0
θ
1
0.077 0 0 0.334
τ 3 0 0 3
Hri 0.79225 0 0 0.57465
Goodness-of-fit test
SSD 0.02428* 0 0 0.06640
Fig. 3. – UPGMA phenogram of genetic relationships among
populations of S. officinalis. Bootstrap estimates (as a percentage)
are indicated above branches. MS, Marmara Sea; AS, Aegean Sea;
NMS1, north-eastern Mediterranean Sea (Antalya Bay); NMS2,
north-eastern Mediterranean Sea (Iskenderun Bay).

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was high for the Marmara Sea (93%) and Iskenderun
Bay (78%) samples (Table 5). The most important
characters for distinguishing the MS sample were
CSD, DBE and MW (Fig. 4 and 5). The most impor-
tant characters in distinguishing the NMS1 sample
were ED and CL.
Cuttlebone chemistry
Univariate statistics (ANOVA) revealed highly
significant differences (P<0.001) among samples
for the 12 elements. The first and second discri-
minant functions contributed 72% and 26% to the
total variance respectively, showing that the major-
ity of total variance was explained by the first two
canonical variables. Plotting all samples on the first
two discriminant functions shows that all samples
are very separate (Fig. 6). The overall assignment
of individuals into their original sample was 100%
(Table 5).
Examination of the contribution of each variable
to the first canonical functions showed a high contri-
bution from Cu, which differentiated the Aegean Sea
samples (Figs. 6 and 7). Cr and Ca contributed to the
second canonical function and separated the Mar-
Table 5. – Euclidean distance between stocks of S. officinalis for
morphometrics (below diagonal) and cuttlebone chemistry (above
diagonal). Numbers in the diagonal (bold) are the percentage
of individuals classified correctly into their original stock by
morphometric / cuttlebone chemistry respectively.
Stock NMS1 NMS2 AS MS
NMS1 43/100 17.847 112.372 46.211
NMS2 83.531 78/100 124.925 56.341
AS 15.827 18.239 50/100 102.348
MS 22.499 24.199 19.561 93/100
Fig. 4. – Confidence ellipses of DFA scores for morphometric
analysis and UPGMA dendrogram based on Euclidean distance. MS,
Marmara Sea; AS, Aegean Sea; NMS1, north-eastern Mediterranean
Sea (Antalya Bay); NMS2, north-eastern Mediterranean Sea
(Iskenderun Bay).
Fig. 5. – Contribution of morphometric characters to the discriminant
functions. Vectors indicate the loadings of the scores for each
variable on the first two discriminant functions. MW, mantle width;
NW, neck width; ED, eye diameter; CSD, club sucker diameter; CL,
club length; DBE, distance between eyes.
Fig. 6. – 95% confidence ellipses of DFA scores for cuttlebone
chemistry and UPGMA dendrogram based on Euclidean
distance. MS, Marmara Sea; AS, Aegean Sea; NMS1, north-
eastern Mediterranean Sea (Antalya Bay); NMS2, north-eastern
Mediterranean Sea (Iskenderun Bay).

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mara and north-eastern Mediterranean Sea (NMS1
and NMS2) samples (Figs. 6 and 7). Mantel’s test
revealed that the Euclidean distance for cuttlebone
chemistry between these populations was not sig-
nificantly associated with geographical distances
(r=-0.30; P>0.05).
DISCUSSION
Genetic, morphologic and cuttlebone chemistry
data from this study showed that there are discrete
populations of S. officinalis in Turkish coastal wa-
ters. However, no haplotypes were shared among
the four populations of S. officinalis, and genetic
variation was not randomly distributed. Analysis
of cuttlebone chemistry also showed many differ-
ences among the four geographic populations of
S. officinalis, which is consistent with the genetic
data. Morphometric data revealed three populations
of S. officinalis along the Turkish coast. Only the
neighbouring populations (NMS1 and AS) showed
morphological similarity, which is not in agreement
with the genetic and cuttlebone chemistry data al-
ready discussed.
Marine species generally show little genetic dif-
ferentiation due to lack of major geographical bar-
riers to dispersal and gene flow (Ward et al., 1994).
Genetic divergence between populations of S. offici-
nalis was found to be considerably high in compari-
son to other marine species, which may be related
to the limited dispersal ability of S. officinalis. Al-
though females fix their eggs to the sea floor, there
is no pelagic larval phase (benthic juveniles hatch
directly from the eggs), and the adults have limited
migratory capacities (Guerra, 1992). All population
pairs separated by distances showed significant dif-
ferences in haplotype frequencies, which indicates
limited genetic exchange among areas. Neverthe-
less, the possibility of these geographically based
genetic patterns resulting from adaptive responses to
different environmental pressures (natural selection)
or due to isolation by distance among populations
cannot presently be excluded. There is evidence of
selection acting on mtDNA genes (Ballard and Kre-
itman, 1995), and thus haplotype diversity may not
always result from a stable neutral distribution. How-
ever, Mantel tests indicate a significant correlation
between geographic and genetic distances, which
suggests that the data fit to an isolation-by-distance
model of gene flow. Therefore, the degree of geo-
graphic isolation in S. officinalis around the Turk-
ish terrestrial waters is consistent with the degree of
genetic differentiation. Similarly, Perez-Losada et
al. (1999) studied genetic variation with microsatel-
lite loci from NE Atlantic and Mediterranean coasts
of the Iberian Peninsula and found highly signifi-
cant subpopulation structuring, consistent with an
isolation-by-distance model of gene flow. Wolfram
et al. (2006) analyzed microsatellite DNA varia-
tion among S. officinalis populations in the English
Channel and the Bay of Biscay, and reported that the
genetic distance between the populations increases
with geographic isolation.
Since mtDNA is a maternally inherited molecule
there may be a differential population structure be-
tween sexes. The ratio of sexes was between 55 and
60% for females within MS, AS and NMS2 popula-
tions. A large percentage of the individuals analyzed
in the NMS1 population were females (80%) (Table
1). The possibility of a differential population struc-
ture between sexes is not valid since all populations
have male individuals in moderate numbers.
Analyses of minor chemical constituents in fish
otoliths have been successfully used to distinguish
specific population differences for stock discrimina-
tion (Campana et al., 1994; Turan, 2006); however,
to our knowledge, there is no study using cuttlebone
chemistry for population identification of cuttlefish.
The most important result of this study is the use
cuttlebone chemistry to successfully identify cut-
Fig. 7. – Contribution of cuttlebone chemistry elements to the
discriminant functions. Vectors indicate the loadings of the scores
for each variable on the first two discriminant functions.

84 • C. TURAN and D. YAGLIOGLU
SCI. MAR., 74(1), March 2010, 77-86. ISSN 0214-8358 doi: 10.3989/scimar.2010.74n1077
tlefish populations in agreement with genetic data.
The method described here allowed 100% correct
identification of cuttlefish specimens into their
original sample based on 12 elements. Examination
of the contribution of cuttlebone chemistry charac-
ters to discriminant functions demonstrates that Cu
strongly contributes to the first discriminant func-
tion (Fig. 7) and plays a major role in discriminating
the north-eastern Mediterranean and Marmara Sea
populations from the Aegean Sea population (Fig.
6). Yazkan et al. (2004) analyzed the chemical con-
tents of some molluscs in Antalya Bay and reported
that cuttlefish contain the highest levels of Cu com-
pared to the other molluscs. Cr and Ca play a role
in discriminating two Mediterranean populations
(Antalya Bay and Iskenderun Bay). Turan (2006)
reported that the highest level of Ca in the otolith
chemistry of Trachurus mediterraneus populations
from Turkish waters is found in the Iskenderun Bay
population. Therefore, the chemical compositions
of local waters which are fed with different river
systems may determine the cuttlebone chemistry of
cuttlefish populations if there is restricted migration
between locations.
The correlation between geographic distance
and Euclidean distance of both cuttlebone chemistry
and morphometrics of S. officinalis was not signifi-
cant. However, morphometric data show more geo-
graphically concordant relationships than cuttlebone
chemistry among the populations, since only the
most geographically isolated populations (MS and
NMS2) could be separated by DFA. The assessment
of the contribution of each morphometric character
to discriminant functions shows that differentia-
tion among populations is association with the club
sucker diameter, club length and eye diameter parts
of the body, which may reflect adaptations to dif-
ferent habitat characteristics in each sea, such as
water flow, depth and turbidity. For example, differ-
ences in club sucker diameter and club length may
be attributed to water flow. In higher water flows,
bigger clubs and club suckers are adapted to hang
on rocks. The Marmara Sea has a higher water flow
than Iskenderun Bay (Ozsoy et al., 1996), and the
mean ratios of the club length and club sucker di-
ameter characters to total length were bigger in the
Marmara population (0.34 and 0.21 respectively)
than the Iskenderun Bay population (0.29 and 0.19
respectively). Moreover, differences in eye diameter
may be attributed to turbidity (Moore, 1950). The
Marmara Sea has less turbid water than Iskenderun
Bay (Besiktepe et al., 1993). In more turbid waters
eye diameter is expected to be small (Moore, 1950).
The mean ratios of eye diameter to total length
were larger in the Marmara population (0.50) than
the Iskenderun Bay population (0.53). The detected
morphological differences between populations
of cuttlefish seem to be differential to the environ-
mental factors. The use of morphologic characters
to identify populations must take into account that
these traits are a result of genetics and environmental
influences. Lombarte and Lleonart (1993) reported
that overall otolith shape is regulated genetically,
and otolith size is influenced by environmental con-
ditions. When two populations are clearly different
in morphological terms, it can be inferred that they
may have genetic differences, may have been dur-
ing their lifetime subject to consistently different
environmental influences, or a mixture of both. The
detected morphologic differences are supported by
genetic and cuttlebone chemistry data which indicate
the adaptation of stocks to different environments
with phenotypic and genetic characters.
The number of unique haplotypes and their spa-
tial distribution are useful for assessing the genetic
structure and gene flow among populations (Hauser
et al., 2001). The pattern of haplotype frequency dif-
ferences observed among all populations appeared
to be related to geographic distances. Therefore, the
detection of unique haplotypes and the spatial distri-
bution of each population may be indicative of the
adaptation of the population in each biotope and the
lack of migration across long distances.
The detected mean haplotype (0.1075) and nucle-
otide (0.000818) diversity of S. officinalis are very
low. The Aegean and Iskenderun Bay populations
in particular showed zero diversity. The relation-
ship between haplotype and nucleotide diversity
provides information on population demographic
history. Low haplotype and nucleotide diversity are
interpreted as recent bottlenecks or a founder event
(Grant and Bowen, 1998). Cuttlefish have a short
life span of around 2 years. Given the short life span,
large inter-annual fluctuations in landings, and the
regular annual migration cycle, it is expected that
marine environment conditions have an important
impact on cuttlefish recruitment and distribution
(Boletzky, 1983). Cephalopod fisheries are expand-
ing on the Turkish coasts, and fish stocks are becom-
ing over exploited. Moreover, pollution in the Izmir
and Iskenderun Bays due to the industrialization of
these two areas is also a major reason for the de-

POPULATION IDENTIFICATION OF SEPIA OFFICINALIS • 85
SCI. MAR., 74(1), March 2010, 77-86. ISSN 0214-8358 doi: 10.3989/scimar.2010.74n1077
cline in marine stocks (Salman and Katag˘an, 2004).
Therefore, the detected low haplotype and nucleotide
diversity may be related to a recent bottleneck due
to the above mentioned environmental pressures,
which is supported by the mismatch analysis.
In comparison with microsatellite and allozyme
data with previous studies (Perez-Losada et al.,
1999, Shaw et al., 1999; Perez-Losada et al., 2002),
mitochondrial DNA restriction fragment length pol-
ymorphism can detect structuring as given by micro-
satellite analysis (Shaw et al., 1999; Perez-Losada et
al., 2002). However, higher levels of polymorphism
were shown in the microsatellite analysis than in the
RFLP. Allozyme is a weak estimator of genetic di-
versity and divergence as reported by Perez-Losada
et al. (1999) in comparison with RFLP and micros-
atellite analysis.
Cuttlebone chemistry is a good estimator of pop-
ulation differentiation, although detected cuttlebone
chemistry differences between populations were
supported by genetic data. Furthermore, cuttlebone
chemistry has greater potential than morphometrics
for stock identification. It identifies populations on a
small geographical scale, which indicates the greater
capacity of cuttlebone chemistry versus morphomet-
rics to detect fine stock structuring.
In conclusion, due to the observed high genetic,
cuttlebone chemistry and morphometric discrete-
ness, the Marmara, Aegean and two north-eastern
Mediterranean (Antalya Bay and Iskenderun Bay)
populations may be considered four self–recruited
populations. The detected significant levels of ge-
netic, cuttlebone chemistry and morphometric dif-
ferentiation among populations imply demographic
differentiation, and demographically separated
populations should be managed and conserved as
separate units (Carvalho and Hauser, 1994). Whilst
this information is relevant to management of the
increasing commercial exploitation of this species,
additional repeat sampling will be needed to estab-
lish if these findings are spatially present and tempo-
rally stable. Moreover, the use of nuclear genes with
different genetic markers such as microsatellites in
these populations would strengthen these findings.
ACKNOWLEDGEMENTS
Thanks are due to the Turkish Academy of Sci-
ences in the framework of the young scientist award
program (TUBA–GEBIP-2005), MKU BAP for
financial support, and Dr. Kemal Sangun for help
in the laboratory. The genetic part of this study was
generated from the MSc thesis of DY.
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