Age, growth, and population structure of the African cuttlefish Sepia bertheloti based on beak microstructure

Abstract

In this study, we explored the feasibility of using the beaks of the African cuttlefish Sepia bertheloti for age estimation and growth analysis. The rostrum sagittal section (RSS) of the lower beak was the most suitable region in the species. It was applied in samples caught off Morocco and Guinea-Bissau between June 2018 and January 2020. A maximum life expectancy of around 14 months was observed (specifically 419 days for cuttlefishes from Morocco and 433 from Guinea-Bissau). The males presented greater longevity, as the maximum age of the females was between 9 and 11 months. Sepia bertheloti showed a negative allometric growth; however, the exponential model better describes each population growth. By sexes, the males of both locations followed an asymptotic growth model while the females exhibited a non-asymptotic growth. The growth rates were different between locations, with the highest values in Guinea-Bissau. The males, in turn, grew faster for both study locations. In Guinea-Bissau, these growth differences were influenced by the hatching season since individuals born between autumn and winter were the fastest-growing. Samples from Morocco did not show growth differences between the hatching season and other seasons. These results indicate that the RSS of lower beaks are suitable for estimating the age, growth pattern, and population structure of Sepia bertheloti .

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Marine Biology (2023) 170:118
https://doi.org/10.1007/s00227-023-04272-7
ORIGINAL PAPER
Age, growth, andpopulation structure oftheAfrican cuttlefish Sepia
bertheloti based onbeak microstructure
AiramGuerra‑Marrero1 · AuroraBartolomé2· LorenaCouce‑Montero1· AnaEspino‑Ruano1·
DavidJiménez‑Alvarado1· JoséJ.Castro1· CatalinaPerales‑Raya2
Received: 9 December 2022 / Accepted: 5 August 2023 / Published online: 25 August 2023
© The Author(s) 2023
Abstract
In this study, we explored the feasibility of using the beaks of the African cuttlefish Sepia bertheloti for age estimation and
growth analysis. The rostrum sagittal section (RSS) of the lower beak was the most suitable region in the species. It was
applied in samples caught off Morocco and Guinea-Bissau between June 2018 and January 2020. A maximum life expectancy
of around 14months was observed (specifically 419days for cuttlefishes from Morocco and 433 from Guinea-Bissau). The
males presented greater longevity, as the maximum age of the females was between 9 and 11months. Sepia bertheloti showed
a negative allometric growth; however, the exponential model better describes each population growth. By sexes, the males
of both locations followed an asymptotic growth model while the females exhibited a non-asymptotic growth. The growth
rates were different between locations, with the highest values in Guinea-Bissau. The males, in turn, grew faster for both
study locations. In Guinea-Bissau, these growth differences were influenced by the hatching season since individuals born
between autumn and winter were the fastest-growing. Samples from Morocco did not show growth differences between the
hatching season and other seasons. These results indicate that the RSS of lower beaks are suitable for estimating the age,
growth pattern, and population structure of Sepia bertheloti.
Keywords Increments· Lower beak· RSS· Daily growth· Cuttlefish
Introduction
The African cuttlefish Sepia bertheloti (Orbigny, 1839) is
distributed in the Eastern Atlantic from the Canary Islands
and Western Sahara to Angola, predominantly occupying
sandy bottoms from 20 to 160m (Jereb and Roper 2005;
Guerra etal. 2014). It can reach sizes of a 180mm man-
tle length for males and 130mm for females (Guerra etal.
2014). This species is caught by bottom trawlers at depths
between 70 and 140m (Roper etal. 1984), with greater fre-
quency in the fisheries operating off the West African coast
(FAO Fishing Area 34). It is one of the most productive
regions of the world (Martos and Peralta 1995; Doumbouya
etal. 2017) due to the upwelling systems off of the West-
ern Sahara, Senegal, and Guinea-Bissau (Berrit and Rebert
1977).
There are no separate capture statistics for S. bertheloti,
as it is often traded together with S. officinalis in Moroc-
can/Saharan waters, with S. hierredda in Guinean waters or
treated as commercial by-catch. Sepia bertheloti accounts
for 11–35% of reported by-catch and is marketed fresh and/
or deep-frozen for export (Jereb and Roper 2005). The target
cephalopod species for the Western Sahara/Morocco area
are Octopus vulgaris, S. officinalis, and Loligo vulgaris
(Hernández García and Castro 1994), while for the Guinea-
Bissau fishing grounds, the target species are O. vulgaris
and S. hierredda (FAO 2021). Furthermore, probably due
to the low density and commercial value, the biological and
fishery information about S. bertheloti is very limited in
comparison to the fishing industry’s cuttlefishes. Most of
this information has been acquired by analyzing the stomach
contents of its natural predators (Delgado de Molina etal.
Responsible Editor: R. Rosa .
* Airam Guerra-Marrero
airam.guerra@ulpgc.es
1 IU-ECOAQUA, Universidad de Las Palmas de Gran
Canaria, Edf. Ciencias Básicas, Campus de Tafira, Las
Palmas de Gran Canaria, 35017LasPalmas, Spain
2 Centro Oceanográfico de Canarias (IEO, CSIC), Calle Farola
del Mar. 38180, SantaCruzdeTenerife, Spain
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Marine Biology (2023) 170:118
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1993; Monzón-Argüello etal. 2018), by conducting explora-
tory fishing campaigns to assess the state of the resources
(Balguerías etal. 1993; Rocha etal. 2017; García-Isarch
etal. 2009; Perales-Raya etal. 2010a), or from the analy-
sis of metal concentrations (Ama-Abasi and Akpan 2008).
However, there is no information about age and growth of
S. bertheloti, which are both key factors in estimating life
history parameters and understanding its population dynam-
ics in order to conduct an appropriate biomass estimation
available for fishing (Arreguín-Sanchez etal. 1996).
The use of indirect methods off growth estimation based
on length–frequency analysis is not suitable for age esti-
mation in cephalopods since they are semelparous species
with short life cycles and high variations among individuals,
making their estimation imprecise (Jackson 2004). Direct
methods using hard structures, such as statoliths, beaks,
lenses, or gladius, based on the study of growth increments
have proven to be the most useful method for estimating
the absolute age and the growth of cephalopods. Growth
increment analysis in jaws has been shown to be an appro-
priate technique for age determination, validated in other
benthic cephalopods, such as O. vulgaris (e.g., Hernández-
López etal. 2001; Canali etal. 2011; Perales-Raya etal.
2014b; Armelloni etal. 2020), O. maya (e.g., Rodríguez-
Domínguez etal. 2013; Bárcenas etal. 2014), or Sepia offici-
nalis (Guerra-Marrero etal. 2023). The recent revision of
Xavier etal. (2022) provides detailed information on the
attempted study of other cephalopod species using beak
increment analysis, as well as those with confirmed daily
deposition and validated ontogenetic stages.
The processing of cephalopod’s hard structures is usu-
ally a time-consuming process, but it enables age estimates
with a high rate of precision and is useful for identifying
seasonal cohorts, an important component of cephalopod
stock assessment. Nevertheless, the great variety of the
growth rates (exhibited by individuals of the same age with
different lengths) makes age-based models impractical for
real-time stock assessment (Arkhipkin etal. 2021). Arkh-
ipkin etal. (2021) propose a range of methodologies for
assessing cephalopod populations, while warning that there
is a high data requirement with a constant catch per unit
effort report (CPUE) required. The abundance estimates of
S. bertheloti in the area encompass other cuttlefish species,
such as S. officinalis for Northwest Africa and S. hierredda
for Central-West Africa (Jereb and Roper 2005); therefore,
age analysis using hard structures is a suitable approach for
future stock assessments.
Based on previous studies of other cuttlefish species, it is
known that sepias have high growth rates (Perales-Raya etal.
1994; Perales-Raya 2001; Bettencourt and Guerra 2001;
Guerra 2006) although size/weight differences have been
observed between the populations of these species along the
large Canary Current marine ecosystem (Hernández-García
and Castro 1994; Hernández-López 2000; Almonacid-
Rioseco 2006; Jurado-Ruzafa etal. 2014).
This study contributes to (i) age and life span estima-
tions of S. bertheloti in wild populations using the beak
microstructure, (ii) the calculation of the hatching periods,
(iii) determining the best model to describe the population
growth pattern, and (iv) assessing the growth rates by sea-
sons, with the final goal of obtaining these data for the future
stock assessment of the African cuttlefish.
Materials andmethods
The sample
A total of 1124 individuals of the African cuttlefish Sepia
bertheloti were collected from June 2018 to January 2020
in two locations of Northwest Africa (449 individuals from
Morocco and 625 from Guinea-Bissau) from commercial
trawlers operating in each study location (Fig.1). The sub-
sequent data sampling is summarized in Table1.
The cuttlefish were immediately frozen at −20ºC after
fishing and remained frozen until they were processed in the
laboratory. Dorsal mantle length (DML) and body weight
(BW) were measured to the nearest 1mm and 0.01g respec-
tively. Sex was noted and maturity stages were identified
according to the macroscopically maturity scale proposed
by ICES (2010) for Sepia officinalis (namely, 0 is undeter-
mined, 1 is Immature, 2a as Developing, 2b is Maturing, 3a
is Mature/Spawning and 3b is Spent). Beak extraction and
measurements were taken according to Perales-Raya etal.
(2010b); Hernández-García (2003), respectively. The indi-
viduals caught in both locations were categorized according
to the capture season (spring, summer, autumn, and winter).
Length–weight relationship
The length–weight relationship (LWR) was calculated using
the equation BW = aDMLb (power function), where a and b
are the regression parameters estimated by linear regression
of the data logarithmically transformed and adjusted by the
least squares method. Student’s t test was used to verify the
‘b’ values to determine whether they have isometric (b = 3)
or allometric (negative allometric b < 3, and positive allo-
metric b > 3) growth.
Beak analysis
After dissection, the beaks were extracted, cleaned, and
stored in distilled water at a temperature of 4ºC, according
to the procedure described by Perales-Raya etal. (2014b).
A beak subsample of 78 specimens from Morocco and
128 from Guinea-Bissau were analyzed. A randomized
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Marine Biology (2023) 170:118
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categorizing process of the specimens was performed by
size range within 5mm of DML for both sexes.
After an analysis of the different regions of the upper
and lower jaws was performed, the rostrum sagittal sec-
tions (RSS) of the lower beak were selected according to
Perales-Raya etal. (2010b; 2014a). Once the beaks were
processed, they were analyzed using a Nikon Microscope
Multizoom AZ100 with a UV epi-illumination attachment
(providing vertical reflected light) and different magni-
fications (100–400x) to observe the growth increments
(Fig.2).
The observed increments were counted twice by the same
trained reader. The coefficient of variation (CV) was used
to estimate the precision of the readings and the reproduc-
ibility of the method. The CV was calculated as the ratio of
the standard deviation over the mean:
Fig. 1 Sampling areas (FAO Fishing Area 34) where the commercial
trawlers caught Sepia bertheloti in Morocco (Tangier zone) (FAO
34.1.11) and Guinea-Bissau (FAO 34.3.13). Exclusive Economic
Zone (EZZ) for Morocco (Tangier zone) and Guinea-Bissau in the
FAO Fishing Area 34 are shaded
Table 1 Number of individuals of Sepia bertheloti analyzed in two
areas of West Africa caught from July 2018 to January 2020
Capture date Morocco Guinea-Bissau
July 2018 234
August 2018 43
September 2018 44
July 2019 42
August 2019 36
September 2019 97
October 2019 78
November 2019 157
December 2019 155
January 2020 178 60
Total 499 625
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where R1 and R2 were the numbers of increments from the
first and the second reading, respectively. R was the average
of the number of increments of the two readings. According
to Campana (2001), to avoid any bias, the mean of CV was
averaged for each study location, and a CV < 7.6% was taken
as valid, with higher values of CV being rejected.
The relationship between the rostral length of lower
beak (LRL) and the number of increments (NI) was cal-
culated to observe the growth of the reading area accord-
ing to the estimated age. The analysis of covariance
(ANCOVA) was carried out to determine possible signifi-
cant differences in LRL–DML and LRL–NI relationships
according to sex and study locations. These relationships
and all the different analysis were performed using the sec-
ond reading (R2) according to Perales-Raya etal. (2010b),
CV
(%)=100 ×
√
(R1−R)2+(R2−R)2
R
who postulate that R2 is more reliable since the reader has
greater experience and practice.
Growth models andgrowth rate estimation
Length-at-age data of Sepia bertheloti were fitted into seven
growth models (lineal, power, exponential, von Bertalanffy,
Gompertz, logistic, and Schnute (a ≠ 0 and b ≠ 0) models).
According to Bolser etal. (2018), model parameters for
von Bertalanffy, Gompertz, logistic, and Schnute were esti-
mated using a non-linear least squares regression and the
Levenberg–Marquardt algorithm, and confidence limits were
placed around parameter estimates in R studio (using the R
packages Ogle 2017; Elzhov etal. 2015; Baty etal. 2015):
• von Bertalanffy growth model (Von Bertalanffy 1938):
L
(t)=L∞
[
1−e−K(t−t0)
]
• Gompertz growth model (Gompertz 1825):
L
(t)=L
∞
e
(
−
(
1
K
)
e−K(t−t0)
)
• Logistic growth model (Ricker 1975):
L
(t)=L∞
[
1+e−K(t−t0)
]−1
• Schnute growth model (Schnute 1981):
L
(t)=
[
Lb
1+
(
Lb
2−Lb
1
)
1−e−a(t−T1)
1
−
e−a(T2−T1)
]
1
∕
b
where L(t) is length (in mm DML) at age t, L∞ is the
maximum average length (in mm DML), K is the growth rate
coefficient (in year −1), and t0 is the theoretical age at which
length is zero (in years). For the Schnute growth model, T1
is the first specified age, T2 is the second specified age, L1 is
length at age T1; L2 is length at age T2, a is the constant rela-
tive rate of relative growth (in year −1), and b is the incremen-
tal relative rate of relative growth (dimensionless). Since the
Schnute model does not calculate the parameter L∞ directly,
the following equation must be used (Schnute 1981):
The parameters L1, L2, T1, and T2 are the same as used in
the Schnute equation previously, while the parameters a and
b are the resulting parameters of the growth model.
The best model for each sex and area was determined
using the Akaike’s information criterion (AIC) (Akaike
1974), transformed to Akaike weight (AICw) (Burnham
and Anderson 2002) and the Bayesian Information Criterion
(BIC) using the “AICcmodavg” package in R (Mazerolle and
Mazerolle 2017). Akaike weights provide relative likelihood
of each model from the tested set of models.
Estimated growth rates for length-at-age relationships
were calculated for each 90-day age class according to the
L
∞=
[
eaT2L2b−eaT 1L1b
eaT2
−
eaT1
]
1
∕
b
Fig. 2 Appearance of growth increments in the rostrum sagittal sec-
tion (RSS) of lower beak in Sepia bertheloti. A tip region with older
increments. B Detail of the growth increments in the posterior region
of RSS with recent increments. Scale bar: 50μm
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Marine Biology (2023) 170:118
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following equations (Forsythe and Van Heukelem 1987;
Gonzalez etal. 1996):
a. Instantaneous relative growth rate, G (% DML d.−1)
b. Absolute growth rate, AGR (mm d.−1)
Hatching date estimation
To study the influence of seasonality on growth, the hatch-
ing date of each cuttlefish was back-calculated according to
estimated age and the date of capture. According to hatch
dates, four seasonal hatching groups were defined: Spring
G
=
lnR
2
− lnR
1
t
2−
t
1
×
100
AGR =
R
2
−R1
t
2−
t
1
(March–May), Summer (June–August), Autumn (Sep-
tember–November), and Winter (December–February).
Kruskal–Wallis test and post hoc Dunn test were used to
describe possible differences between hatching seasons.
The normal distribution of the data was checked using the
Shapiro–Wilk test in each analysis. When the data showed
a normal distribution, a two-group independent t test was
used to compare differences in age according to the loca-
tion and differences in age by sex. ANCOVA was also used
to analyze differences between locations and sexes. When
a normal distribution was not achieved, a non-parametric
Kruskal–Wallis test and a Dunn post hoc test were used.
All statistical analyses were carried out using R v-4.1.1 (R
Core Team 2022).
Results
Size–structure
Cuttlefish lengths and weights from Morocco and Guinea-
Bissau are shown in Table2. Mature males from Morocco
ranged from 50 to 130mm DML while mature females
ranged from 60 to 110mm (Fig. 3). Guinea-Bissau’s
mature males fell within a range off 60–176mm DML,
while mature females ranged from 68 to 140mm (Fig.4).
Immature and developing/maturing individuals were not
Table 2 Ranges of Dorsal Mantle Length (DML) and Body weights
(BW) of Sepia bertheloti caught in Morocco and Guinea-Bissau
Area Sex DML (mm) BW (g)
Morocco Females 60–120 21.87–127.87
Males 50–138 18.94–206.98
Guinea-Bissau Females 32–168 20.03–314.00
Males 60–176 28.44–456.61
Fig. 3 Dorsal Mantle Length
(DML) frequency distribu-
tion for the sample of Sepia
bertheloti females (n = 102)
and males (n = 397) caught off
Morocco
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found in Morocco (Fig.3), while all reproductive stages
were found in Guinea-Bissau (Fig.4).
The regression parameters of the DML–BW rela-
tionship (power equation) for males and females from
Morocco and Guinea-Bissau are shown in Table3.
The ANCOVA test showed significant differences
in DML–BW relationships between sex and locations
(p < 0.0001). Males of both locations were larger and
heavier than the females, and the specimens from Morocco
were smaller and lighter than those from Guinea-Bissau.
In terms of growth, the LWRs exhibited negative
allometry (See Table3) for both sexes and locations. This
growth model implies a faster growth in DML than in BW.
Age analysis
Of the 206 beaks analyzed, 183 allowed a reliable read-
ing. Twenty-three beaks (11.17%) were discarded due to
malformations (see image in supplementary material) or
severe damage during grinding that made a reliable reading
impossible. Of the 183 beaks, 69 belonged to cuttlefish from
Morocco (Table4) with 114 belonging to specimens taken
from Guinea-Bissau (Table5).
From the Morocco sample, the youngest specimen was a
female (111days old, 60mm DML), and the oldest speci-
men was male (419days, 140mm DML). No significant dif-
ference in age was found between sexes (t test:p = 0.09034),
with the median age being 186 ± 41days in females and
220 ± 70days in males. The oldest specimen was caught in
Fig. 4 Dorsal Mantle Length
(DML) frequency distribu-
tion for the sample of Sepia
bertheloti females (n = 194)
and males (n = 431) caught off
Guinea-Bissau
Table 3 Statistical parameters
of the Dorsal Mantle Length
(DML) and Body Weight (BW)
relationships for females, males
and all individuals caught in
Morocco and Guinea-Bissau
*a− negative allometry
DML–BW relationship R2Confidence interval of b Growth model*
Morocco
Females
BW = 0.4813DML2.3012
0.903 2.1701–2.4323 a–
Males
BW = 0.414DML2.3576
0.934 2.2973–2.4179 a–
All
BW = 0.4433DML2.3303
0.932 2.2774–2.3832 a–
Guinea-Bissau
Females
BW = 0.4619DML2.3183
0.922 2.2058–2.4308 a–
Males
BW = 0.266DML2.5662
0.962 2.5147–2.6177 a–
All
BW = 0.3296DML2.4757
0.952 2.4297–2.5216 a–
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Marine Biology (2023) 170:118
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summer 2018, while the youngest was caught during winter
2020 (see Table4). Mature females were found between 111
and 234days while the mature males were found between 11
and 370days (see Fig.5).
Cuttlefishes from Guinea-Bissau showed an estimated age
between 94 and 433days, with a mean age of 219 ± 74days.
The youngest specimen was a 94-day-old female (72mm
DML), and the oldest specimen was a 433-day-old male
(160mm DML). The youngest male was 122days old
(85mm DML), and the oldest female was 316days old
(152mm DML). Statistically significant difference in age
was found between the sexes (t test:p = 0.0082), with a mean
age of 198 ± 56days in females and 235 ± 78days in males.
The oldest specimen was caught in summer 2019, while the
youngest individual was caught during the fall of the same
year (see Table5). Mature females were found between 126
and 289days while the mature males were found between
118 and 400days (see Fig.6).
No significant difference in age was found between
locations (t test:p = 0.3285) and sexes (t test: p = 0.784 for
females and p = 0.354 for males). The mean reading preci-
sion value (CV) off the beaks readings was 2.72 ± 3.95% for
specimens from Guinea-Bissau and 2.61 ± 3.54% for speci-
mens from Morocco. Correlations between NI, LRL, and
DML for both locations are shown in Table6. In Morocco,
the relationship between LRL and DML for both sexes was
Table 4 Descriptive statistics for Sepia bertheloti females, males and total sample collected throughout different seasons off Morocco
NI number of growth increments, DML dorsal mantle length, BW body weight, X mean, SD standard deviation
Capture season N NI (days) DML (mm) BW (g)
Min. Max. X ± SD Min. Max. X ± SD Min. Max. X ± SD
Morocco
Females
Summer ‘18 13 144 267 212.62 ± 39.12 70 110 88.31 ± 12.34 35.7 96.52 69.19 ± 19.14
Autumn ‘18 2 187 204 195.50 ± 12.02 90 96 93.00 ± 4.24 65.93 83.46 74.70 ± 12.40
Winter ‘20 8 111 240 184.75 ± 42.35 60 12 91.13 ± 20.88 30.82 127.87 80.75 ± 34.86
Males
Summer ‘18 29 149 419 237.24 ± 65.34 75 140 106.62 ± 14.16 45.19 192.85 110.01 ± 36.04
Autumn ‘18 8 137 383 204.25 ± 76.81 82 133 106.38 ± 16.66 50.38 175.8 107.71 ± 40.14
Winter ‘20 9 114 410 231.13 ± 107.19 60 138 99.11 ± 28.03 26.29 202.37 104.04 ± 66.01
Total
Summer ‘18 42 144 419 229.62 ± 59.13 70 140 100.95 ± 15.96 35.7 192.85 97.37 ± 36.87
Autumn ‘18 10 137 383 202.5 ± 67.96 82 133 103.70 ± 15.80 50.38 175.8 101.10 ± 38.26
Winter ‘20 17 111 410 207.94 ± 82.30 60 138 95.35 ± 24.50 26.29 202.37 93.08 ± 53.42
Table 5 Descriptive statistics for Sepia bertheloti females, males and total sample collected throughout different seasons off Guinea-Bissau
NI number of growth increments, DML dorsal mantle length, BW body weight, X mean, SD standard deviation
Capture season N NI (days) DML (mm) BW (g)
Min. Max. X ± SD Min. Max. X ± SD Min. Max. X ± SD
Guinea-Bissau
Females
Summer ‘19
Autumn ‘19 25 94 316 201.28 ± 57.04 70 152 103.2 ± 17.51 44.93 258.74 107.89 ± 44.32
Winter ‘20 12 102 301 213.16 ± 55.91 60 132 101.17 ± 20.25 21.8 174.65 105.22 ± 44.20
Males
Summer ‘19 31 174 433 269.48 ± 75.60 126 170 145.29 ± 11.25 172 393.34 270.93 ± 57.94
Autumn ‘19 25 118 400 219.84 ± 77.35 60 173 114.84 ± 30.01 34.09 351.39 140.29 ± 86.49
Winter ‘20 21 122 372 234 ± 74.06 65 175 115.43 ± 29.74 30.04 383.86 151.13 ± 94.35
Total
Summer ‘19 31 174 433 269.48 ± 75.60 126 170 145.29 ± 11.25 172 393.34 270.93 ± 57.94
Autumn ‘19 50 94 400 210.56 ± 67.91 60 173 109.02 ± 25.02 34.09 351.39 124.09 ± 69.96
Winter ‘20 33 102 372 226.48 ± 67.88 60 175 110.24 ± 27.25 21.8 383.86 134.43 ± 82.09
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Marine Biology (2023) 170:118
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best fitted by the exponential model (Table6). Moreover,
the exponential model was the best model to describe the
relationship between LRL and NI (Table7). ANCOVA
showed that there were statistically significant differences
between the sexes with respect to the DML–LRL relation-
ship (p = 0.022), but no significant differences were found in
Fig. 5 Age frequency distribu-
tion for females (n = 23) and
males (n = 46) of Sepia berth-
eloti caught off Morocco
Fig. 6 Age frequency distribu-
tion for females (n = 37) and
males (n = 77) of Sepia berth-
eloti caught off Guinea-Bissau
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Marine Biology (2023) 170:118
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the LRL–NI relationship (p = 0.587). Also, in the LRL–NI
relationship, greater variability was observed in males than
in females, which resulted in lower R2values. In the case of
Guinea-Bissau for both sexes, the relationship between LRL
and DML was best described by a linear model (Table7).
In the case of females, the best LRL–NI relationship fits
the linear model, while this relationship in males was best
described by the power model (Table7). ANCOVA showed
that there was a statistically significant difference in the
DML–LRL relationship of both sexes (p = 0.001) but not in
the LRL–NI (p = 0.155) relationship. A greater variability
of the DML–LRL and LRL–NI relationships was observed
in males than in females, which resulted in lower R2values
observed in samples from Morocco.
Growth models andgrowth rates
The estimated statistical parameters for the different growth
models are shown in Table8. According to AIC parameters,
the Schnute and the exponential models best described the
Table 6 Pearson’s correlation
coefficients for Morocco and
Guinea-Bissau.
DML dorsal mantle length, LRL lower rostral length, NI number of increments
Morocco Guinea-Bissau
R p value Correlation r p value Correlation
LRL–DML 0.45 < 0.001 + 0.81 < 0.001 +
NI–LRL 0.48 < 0.001 + 0.66 < 0.001 +
NI–DML 0.77 < 0.001 + 0.84 < 0.001 +
Table 7 Statistical parameters of the Dorsal Mantle Length (DML)
and Lower Rostral Length (LRL) according to the numbers of incre-
ments (NI) observed in males and females caught in Morocco and
Guinea-Bissau
Area Equations R2
Guinea-Bissau
Females
DML = 32.499LRL + 8.9974
0.600
LRL = 0.0059NI + 1.7166
0.580
Males
DML = 32.114LRL + 25.17
0.630
LRL = 0.2698NI + 0.4569
0.410
Morocco
Females
DML = 36.36e0.4235LRL
0.563
LRL = 1.414e0.0023NI
0.568
Males
DML = 34.297
e
0.483LRL
0.500
LRL = 1.945e0.0008NI
0.430
Table 8 Statistical parameters
of different growth model fitted
to Sepia bertheloti Dorsal
Mantle Length-age data from
Morocco and Guinea-Bissau
AIC akaike’s information criterion, AICw akaike’s weight, BIC bayesian information criterion. K: number
of parameters in each model. Best growth model fit is given in bold underlined
Model Dorsal Mantle Length–age data
Males Females All
AIC AICw BIC AIC AICw BIC AIC AICw BIC
Morocco
Logistic 412.32 0.02 420.27 233.80 0.17 239.27 655.50 0.10 665.18
Gompertz 411.49 0.03 419.44 234.13 0.14 239.60 654.81 0.14 664.18
von Bertalanffy 410.58 0.04 418.58 234.47 0.12 239.94 654.24 0.19 663.91
Schnute 404.55 0.86 410.52 234.95 0.09 239.05 660.96 0.01 668.22
Power 424.15 0.00 430.12 235.51 0.07 239.61 666.56 0.00 673.82
Linear 419.69 0.00 425.66 234.18 0.14 238.28 660.46 0.01 667.72
Exponential 410.28 0.05 416.24 232.86 0.27 236.96 652.09 0.55 659.35
Guinea-Bissau
Logistic 564.01 0.13 572.89 229.41 0.10 235.02 833.29 0.06 843.67
Gompertz 562.61 0.27 571.49 229.25 0.10 234.85 832.25 0.10 842.63
von Bertalanffy 561.40 0.48 570.29 229.09 0.12 234.69 831.31 0.16 841.69
Schnute 577.82 0.00 284.48 253.98 0.00 258.19 858.34 0.00 866.13
Power 583.70 0.00 590.36 228.90 0.13 233.10 842.14 0.00 849.93
Linear 577.00 0.00 583.66 228.18 0.19 232.38 834.98 0.03 842.76
Exponential 564.21 0.12 570.88 226.84 0.36 231.04 828.54 0.65 836.33
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Marine Biology (2023) 170:118
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growth pattern of males and females, respectively, in the
Morocco population. The exponential model was the best
to describe the growth of the entire population (combin-
ing males and females). In the case of Guinea-Bissau’s
Sepia bertheloti population, the von Bertalanffy model best
described the growth pattern of males and the exponential
model for females, while for the entire population (males
and females combined), the exponential model showed the
best fit. Figure7 shows the best growth curves for males and
females of each study location.
The asymptotic length (L∞), according to the Von Ber-
talanffy model for males from Guinea-Bissau, was 173mm
DML, and according to the Schnute model, the males from
Morocco showed a L∞ of 140mm DML.
The largest number of specimens was aged from 191
to 280days (Table8), for Morocco (51.47%) and Guinea-
Bissau (41.22%), with the youngest age classes (< 100days
old) being the least present (Morocco: 0.00% and Guinea-
Bissau: 0.88%). In the case of males, the lowest instantane-
ous relative growth rate (G) values were for the age classes
of 281–370 and > 371days old for Morocco and Guinea-
Bissau, respectively. In the case of females, the lowest
G values were for the 191–280days old age classes for
Guinea-Bissau. The fastest growth patterns were found in
the lower age classes of 191–280 for males from Morocco
and Guinea-Bissau, while for females, it was in the range
of 101–190days old for Guinea-Bissau. Females from
Morocco have not been compared since just obtaining a
value of G could misrepresent their results. Even so, the age
range available for Morocco females (191–280days old)
exhibited a lower G than individuals of the same age from
Guinea-Bissau. This also occurs for males as, those from
Guinea-Bissau show a higher G for all age classes, except for
individuals > 371days old, where cuttlefishes from Morocco
show a value of 0.137% DML d−1 and those from Guinea-
Bissau a value of 0.131% DML d−1. In Table9, all G and
AGR data are summarized.
Significant differences in G and AGR growth rates
between sexes (t test, p < 0.0001) and locations (t test,
p < 0.0001) were found. The individuals from Guinea-Bissau
showed a higher G value than the individuals from Morocco,
showing faster growth at the same age (See Table9). On the
other hand, within each location, males had a higher growth
rate than females. This is demonstrated by the fact that males
showed larger sizes than females in both locations for the
same age. The differences in G and AGR between locations
are observed: individuals from Guinea-Bissau showed larger
sizes than individuals from Morocco at the same age ranges.
Hatching season
The back-calculation method indicated that the cuttle-
fish hatched between June 2017 and September 2019 for
Morocco, and between May 2018 and October 2019 for
Fig. 7 Best growth models fitted to Dorsal Mantle Length at age data for females (asterisks), males (circles) and all individuals of Sepia berth-
eloti caught off Morocco (left) and Guinea-Bissau (right)
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Marine Biology (2023) 170:118
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Guinea-Bissau. It was observed that cuttlefish hatched
throughout the year in Morocco (Fig.8A) and Guinea-
Bissau (Fig.8B); however, 45.59% of the total sample
hatched in winter for Morocco, while Guinea Bissau’s
the hatchings had two marked peaks—one in summer
(30.70%) and another in winter (35.08%). Kruskal–Wallis
test (W = 4.0462, p = 0.2565) did not result in significant
differences in length ranges according to season of hatch-
ing for individuals from Morocco. In contrast, individuals
from Guinea-Bissau showed significant differences in length
ranges (Kruskal–Wallis test; W = 36.439, p < 0.0001). The
post hoc Dunn test (p < 0.001) showed that these differences
were due to the fact that individuals born during warm sea-
sons (spring and summer) were smaller than those born in
the autumn/winter. Individuals hatched in winter exhibited
the largest sizes.
Growth rates for each hatching season group were ana-
lyzed for females and males separately (see supplementary
material). In Morocco, the highest values of G for males
and females were found for specimens born in summer, and
for Guinea-Bissau, the highest values of G were found in
autumn for females and in spring for the males. In both loca-
tions and sexes, a decreasing trend in the growth rhythm was
observed with age.
Discussion
In this study, the length ranges obtained from commercial
fisheries did not enable us to separate the catches into dif-
ferent ontogenetic groups (juveniles and adults) due to the
lack of consensus regarding definition the juvenile phase.
Sweeney etal. (1992) assigned the category of “juveniles” to
the stage of development between hatching and the subadult
stage (defining the category of “subadult stage” as that stage
in which the morphological characteristics of cephalopod
are sufficiently developed to determine the species and end-
ing when sexual maturity is reached). Bellanger etal. (2005)
defined the juvenile category for Sepia officinalis as indi-
viduals up to 3months old.
Significant differences in mean length between the sexes
have already been described for other cuttlefish, such as
Sepia latimanus, S. koilados, S. rhoda, and S. subplana
(Bettencourt and Guerra 2001; Dan etal. 2012), white males
being larger than females. However, this is not a character-
istic that can be extrapolated to the whole Sepiidae family
since most species have a different growth pattern where
females are larger than males (i.e., S. orbignyana and S.
elegans among others; Jereb and Roper 2005).
Differences in growth conditioned by environmental
factors (i.e., latitude, temperature, food, etc.) have been
described in cephalopods (e.g., Arkhipkin etal. 1998; Sem-
mens etal. 2004; Guerra 2006; Batista etal. 2021). In the
case of S. bertheloti, it was observed that specimens from
Guinea-Bissau (Central Africa) exhibited larger sizes than
individuals captured in Morocco (North Africa) at the same
age. The oceanographic differences of both zones, due to
the influence of high productivity from the Western Sahara
upwelling (Arístegui etal. 2009) and the different ther-
mal ranges between the locations due to the seasonality of
upwellings and winds (Arístegui etal. 2009; Pelegrí etal.
2017), might cause differences in the length frequency dis-
tribution. In relation to growth, males and females showed
negative allometric patterns, growing faster in dorsal mantle
length than in total weight, which is comparable to other
species of cuttlefish such as S. officinalis (Vasconcelos etal.
2018).
Table 9 Dorsal mantle length
growth rates for each age class
of Sepia bertheloti females
and males from Morocco and
Guinea-Bissau
Highest value ofG is given in bold
G instantaneous relative growth rate (% DML d−1), AGR absolute growth rate (mm d−1), X average, SD
standard deviation
Age class (Days) Morocco Guinea-Bissau
DML G AGR DML GAGR
X ± SD X ± SD
Females
 < 100 72.00 ± 0.00 – –
101–190 81.78 ± 16.27 – – 94.38 ± 15.24 0.402 0.332
191–280 100.71 ± 13.89 0.147 0.141 107.5 ± 12.29 0.182 0.183
281–370 129.25 ± 16.40 0.288 0.340
Males
101–190 89.6 ± 15.51 – – 93.52 ± 21.45 – –
191–280 108.52 ± 9.97 0.281 0.277 130.42 ± 13.58 0.455 0.505
281–370 123.67 ± 6.62 0.129 0.149 146.79 ± 12.77 0.144 0.199
 > 371 137.00 ± 3.61 0.137 0.179 166.50 ± 4.76 0.131 0.205
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Marine Biology (2023) 170:118
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In this study, the analysis of beak microstructure for Sepia
bertheloti used rostrum sagittal sections to determine age.
This is in contrast to other benthic cephalopods, such as
Octopus vulgaris (e.g., Perales-Raya etal. 2010b; 2014a, b;
Canali etal. 2011; Cuccu etal. 2012), O. insularis (Batista
etal. 2021), or O. maya (Rodríguez-Domínguez etal. 2013)
where the lateral wall surfaces (LWS) of upper beaks were
successfully used for age estimation. In the case of S. berth-
eloti, and after exploring the RSS and LWS of several upper
and lower jaws, the RSS of the lower beak showed the
Fig. 8 Frequency distribution of back-calculated hatching months for Sepia bertheloti from A Morocco and B Guinea-Bissau
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Marine Biology (2023) 170:118
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clearest pattern of growth increments. On the contrary, no
clear sequence of growth increments were observed for age
estimation of S. bertheloti in the LWS of the upper beaks.
Although differences were observed among the length
distributions of specimens within the same age classes
of both studied locations, the maximum age recorded for
Sepia bertheloti (14months) did not differ between loca-
tions. Nevertheless, according to our data, males showed a
higher life span than females in both locations. The maxi-
mum estimated age for males was 14months, while females
showed a maximum age of 9–10months. As samples do
not cover the entire year in the northern location, some of
the largest individuals may not have been caught; therefore,
the maximum age could be underestimated. In this context,
using age data from statoliths, Perales-Raya (2001) obtained
a maximum age of 223days (over 7months) for both sexes
for S. hierredda from Western Sahara, with males reach-
ing larger sizes than observed in this study. Bettencourt and
Guerra (2001) showed that the maximum age of S. offici-
nalis under culture conditions was 420days (14months),
although the number of increments in the statoliths could
have been underestimated due to the large number of narrow
increments close to the nucleus, which were very dark and
difficult to detect and discern. While working with samples
from the English Channel, Challier etal. (2005) reported
an approximate life expectancy of 2years for S. officinalis.
Similarly, Nabhitabhata and Nilaphat (1999) described the
life expectancy of S. pharaonis as one year or over two
years depending on the season of birth. This characteristic
of life expectancy was also described by Hernandez-López
(2000); life span variations in O. vulgaris are dependent on
the hatching season. Our results indicate life span of around
one year for S. bertheloti in both fishing locations, although
it should be noted that this age range corresponds to speci-
mens captured by commercial fishing fleets. Additionally, a
deeper study of both populations would be advisable in order
to observe possible differences in life expectancy and sexual
maturity as reported for other species (Moreno etal. 2002).
The use of asymptotic models for the growth analysis
in cephalopods is something that has been under discus-
sion for years. Several studies, e.g., Jackson etal. (2000),
describe the inefficiency of the von Bertalanffy model for
cephalopods. In contrast, authors such as Uozumi andShiba
(1993) or Brodziak and Macy (1996) recommend the use of
the Gompertz and Schnute asymptotic models (Petric etal.
2021). Arkhipkin and Roa-Ureta (2005); Arkhipkin etal.
(2021) recommend using the Schnute model to describe
growth since the use of von Bertalanffy parameters for
assessment models is inappropriate for cephalopods’ semelp-
arous classification. In this study, seven growth models were
tested, including four with asymptotic growth (Logistic, von
Bertalanffy, Gompertz, and Schnute models). The absence
of individuals of small and very large lengths means that
our growth models were adapted to the fished portion of the
population. Forsythe and Van Heukelem (1987) indicated
that cephalopods grow differently in each life stage, so the
presence of extreme length ranges determines which model
fits best. According to the length distributions in our sam-
ple, the exponential model was the one that best described
the growth of the S. bertheloti population of Morocco and
Guinea-Bissau, which has also been described as adequate
for other cephalopods species during the early stages of their
life cycles (Forsythe and Van Heukelem 1987). However,
the exponential model was not the best model to consider to
each sex separately. The females, with a shorter maximum
age, showed an exponential growth pattern, but the asymp-
totic models (Schnute’s for males from Morocco and Von
Bertalanffy’s for males from Guinea-Guinea) was a better
fit for males. This variation in growth between males and
females may be due to life expectancy factors, since males
have a longer life span than females and are probably able to
survive a longer after reproduction. Furthermore, an asymp-
totic model in the final phase of life would be expected as
the growth rate slows.
The instantaneous growth rates generally showed high
values in the early stages of life and are expected to decrease
with age. Many authors have already observed this growth
pattern in cephalopods (Richard 1971; Dominguez etal.
2006; Petric etal. 2021 among others). Cuttlefish from
Guinea-Bissau showed higher growth rates than those from
Morocco in the same age bracket, although differences in
date of capture might affect this. By sexes, males from both
locations exhibited a longer life span than females. These
differences between sexes and geographic locations have
also been observed in other cephalopods such as Illex coin-
detti (Arkhipkin 1996) where females grow faster than males
and specimens from Central Africa (Sierra Leone) grow
faster than those from the Western Sahara. These observa-
tions are in keeping with the hypothesis that individuals
from colder waters (i.e., Morocco) have a longer life span,
a slower growth rate and later reproduction than cuttlefish
from warmer waters (i.e., Guinea-Bissau), as suggested by
several authors (e.g., Hernández-García and Castro 1998;
Pelegrí etal. 2017).
Regarding growth differences by hatching season,
specimens from Guinea-Bissau born during the warmer
seasons (spring and summer) had smaller lengths at a
given age than individuals born during the autumn and/or
winter periods. Conversely, in the cuttlefish S. hierredda
from the Western Sahara, the specimens born in spring
showed larger sizes at a given age than those born in
autumn (Perales-Raya 2001), though it should be noted
that the author also found inter annual differences. The
back-calculation analysis showed that S. bertheloti from
Morocco and Guinea-Bissau hatch continuously through-
out the year. A peak of hatching was observed in the
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Marine Biology (2023) 170:118
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winter off of Morocco, but two marked peaks were shown
in Guinea-Bissau, one in summer and one in winter. These
results should be considered with caution when managing
these populations that are difficult to access as the sampled
period does not cover the whole year, since a more com-
plete study (> 18months of sampling) would be neces-
sary to confirm the hatching peaks. However, a continuous
spawning has been observed for many benthic cephalo-
pods, such as O. vulgaris, S. officinalis, and S. hierredda,
in West Africa: however, like the Guinea-Bissau sample,
they usually had two marked reproductive periods (Hatan-
aka 1979; Jurado-Ruzafa etal. 2014). In both locations,
it was observed that the highest G values coincided with
the greatest intensity of the upwellings (Ingham 1970;
Arístegui etal. 2009), when the increased availability of
nutrients at hatching makes cuttlefishes grow faster.
In conclusion, the RSSs of beaks are suitable struc-
tures for age estimation in cuttlefish. The results obtained
from this study suggest that the life span of S. bertheloti
is around 9–10months for females and 14months for
males, with differences between the growth rates likely
due to genetic, environmental and geographical factors,
in keeping with observations off other cephalopod spe-
cies (Guerra 2006). The growth of S. bertheloti showed a
negative allometry following an exponential model in both
study locations. By sex, this model was the best fit for all
the females of the study. However, in the case of males, the
Schnute model was the best adapted to Moroccan males
with the von Bertalanffy model being best suited to the
Guinea-Bissau sample. Growth rates were also different
between locations and sexes. In both locations, males
showed a faster relative instantaneous growth pattern
than females. The population of Guinea-Bissau presented
a higher overall growth rate than Morocco. In Guinea-
Bissau, a sample’s hatching season marked a difference
in growth patterns with individuals born in spring and
summer being smaller than those born in autumn–winter.
In contrast, no size differences were observed in relation
to the hatching season in Morocco. Future efforts should
be focused on accessing a wider range of lengths, seasons,
and maturity stages among S. bertheloti to enhance under-
standing of their life cycles in the region. This information
may enable the analysis of potential differences related
to the water temperature and the influence of upwellings.
This knowledge is indeed essential for the sustainable
management of cuttlefishes in the Central Eastern Atlantic.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s00227- 023- 04272-7.
Acknowledgements AG-M was supported by a PhD-fellowship
(PIFULPGC-2017- CIENCIAS-2) from the University of Las Palmas
de Gran Canaria. CP-R would like to thank the support of the IEO
project EPAFRIK-BIO2.
Author contributions All the authors contributed to the study concep-
tion and design. Material preparation, data collection, and analysis
were performed by AGM, CPR, and JJC. AB greatly contributed to
the material preparation. Data collection was also carried out by LCM,
AER, and DJA. The first draft of the manuscript was written by AGM,
and all the authors commented on previous versions of the manuscript.
All the authors read and approved the final manuscript.
Funding Open Access funding provided thanks to the CRUE-CSIC
agreement with Springer Nature. Guerra-Marrero was supported by a
PhD-fellowship (PIFULPGC-2017-CIENCIAS-2) fromthe University
of Las Palmas de Gran Canaria.
Data availability The datasets generated during and/or analyzed during
the current study are not publicly available due to are being processed
for further analysis but are available from the corresponding author on
reasonable request.
Declarations
Conflict of interest The authors have no relevant financial or non-fi-
nancial interests to disclose.
Ethical approval No applicable.
Consent to participate No applicable.
Consent to publish Not applicable.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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