Spicara Maena Stock Discrimination in Northern Tunisian Waters Drawn on Otolith Shape Analysis

The stock concept is one of the most fundamentals in fishery management. With the development of new analytical methods, a growing number of studies have documented the existence of bio-complexity in discrete populations within areas previously considered to have a single stock managed. Mechanical mixing of populations, with limited interbreeding, may result from an overlap in distribution range, for example, due to seasonal spawning/ feeding migrations [1,2]. Failure to take stock mixing into account in fisheries management, particularly when the stocks differ in productivity, may lead to sub-optimal exploitation and ultimately over-fishing of some stock components [3]. Therefore, efficient stock discrimination methods are needed. Several analytical techniques have been used for stock discrimination, ranging from morphometric otolith microstructure analysis [4] and otolith microchemistry [1,2] to molecular tools [5] and otolith shape analyses [6,7]. Because of the high cost associated with molecular tools and thanks to the availability of otolith samples from extensive historical archives in fisheries research institutes, otolith shape analysis has recently gained interest among fisheries biologists. Otolith shape is known to depend on the interplay between genetic and environmental factors [8]. Separation of populations in both time and space induces divergent otolith shape patterns [9]. Consequently, otolith shape analysis can be a powerful tool in fish stock management. It is already implemented in stock assessment for example for North Sea herring. Otoliths are routinely used to determine age and growth in teleost fishes, but the otolith shape is also an important tool in stock management [10].

Indeed, several otolith shape studies have been concerned with stock discrimination [11- 13] and, to a lesser extent, species differentiation [14]. It has been shown that otolith shape is affected by the interplay of environmental, ontogenetic, and genetic influences [8,15]. Therefore, otoliths have both a phenotypic and a genotypic influence, which strengthens their use as a tool in stock discrimination analyses [16]. Otolith shape can be based on identifiable points or landmarks used to describe morphometric measurements such as perimeter, length and width. However, otoliths usually show complex shapes, and a single set of landmarks is often not sufficient to accurately describe their outlines. In the last decade, though, and thanks to advances in image processing technology and computing power, the use of otolith morphometry has received widespread attention. Spicara maena is a commercial species inhabiting the Mediterranean and the Black Sea [17]. It is also found along the European and African coast of the Atlantic Ocean, from Morocco to Portugal and the Canary Islands [17], and very frequently in the western Algerian coastal waters (Figure 1). This species commonly resides on Posidonia beds and sandy or muddy bottoms up to 100m depth [18]. S. maena feeds primarily on zooplankton [19]. It is often caught at depths ranging from 100 to 150m (personal observation) mostly with trawls or trammel nets [20].

Figure 1:Sampling sites of Spicara maena in the north of Tunisia (Zarzouna; Cap Zbib; Ghar El Melh)

Published works on S. maena focused on several aspects including growth, feeding habits, morphological differentiation and molecular differentiation [21-23]. However, investigations of the stock biology of this species remain scarce and limited to reports on Tunisian waters. In North African waters, for instance, works are only concerned with the study of the feeding habits of S. maena. The study aims to discriminate the stock of this species for the first time in the Mediterranean. Blotched picarel Spicara maena fish stock discrimination and assessment were conducted using the shape of sagittal otoliths. Otolith morphology is influenced by biotic and abiotic factors [8] and analysis of the outline of otoliths has previously been used for stock discrimination [6,24-27]. Based on the homogeneous sample collection, this study focuses on three species of samples collected from the northern waters of Tunisia.

Sampling collection

Table 1:Mean±Standard Deviation (SD) values of the standard length (TL) and ranges of Spicara maena individuals examined from the region of Bizerte: Cap Zbib; Zarzouna and Ghar El Melh.

The samples were collected in the north of Tunisia, particularly in the delegation of Bizerte, in three landing sites: Zarzouna, Ghar El Melh, and Cap Zebib (Figure 1). Simple homogeneous adults, (Same size rang), those that reached sexual maturity (Table 1), were captured with artisanal fishing gear in June 2020 from the northern commercial fishery of Tunisia (Region of Bizerte: S1. Cap Zbib, S2. Zarzouna and S3. Ghar El Melh) (Figure 1). A total of three samples of Spicara maena were collected and measured (total length; TL in mm and total weight; TW in g) (Table 1). The sagittal otoliths were removed, washed, dried and stored in labelled plastic vials. Otoliths from the left side of the fish were oriented with the inner side (sulcus acusticus) up and digitized using a digital camera (Canon IXUS 185 camera) and then passed to an image analyzer. All images included an embedded millimeter scale.

Stock discrimination

Otolith shape analysis: The obtained images of the otoliths (Figure 2) were stored in a database to be processed with the software SHAPE Ver. 1.3. Shape is widely used to analyze the images of the shape of otolith (Figure 1) and to compute their elliptical Fourier descriptors EFDs. The outlines of the contour shape of each otolith were evaluated by Elliptic Fourier Analysis (EFA) as previously described by Mejri [25,28]. The FDs technique describes the outline based on harmonics and generates 17 harmonics per otolith. Each harmonic consists of four coefficients (A, B, C, and D), corresponding to the sine and cosine values of the variation in the X and Y coordinates and resulting in 68 coefficients for each otolith generated by projection of each point of the outline on the X and Y axes (Table 2). The four Fourier Descriptors (FDs) were normalized using the first harmonic to make them constant with changes in size, location, rotation and starting point. After transformation, the first three FDs of the first harmonic were fixed at fixed values (a=0, b=0 & c=0) and were therefore discarded in the analysis. Therefore, each otolith sample was represented by 65 subsequent coefficients. The required number of harmonics for the best reconstruction of the otolith outline, the Fourier Power (FPn), the per cent Fourier Power (FP%), and the cumulative per cent Fourier Power (FPn% cumulative) were calculated according to the following formulas:

where A_n, B_n, C_n, and D_n are the Fourier coefficients.

Cumulative percentage of Fourier Power

Then, the cumulative Fourier mean power was calculated to fix the number of harmonics. A threshold of 99.99% of the total power was chosen to determine the number of harmonics required.

Figure 2:Scheme showing the procedure for obtaining shape.

Table 2:The number of harmonics required in this study.

Data analysis: Analysis of Variance (ANOVA) was performed to assess the significance of differences in the mean values of Standard Length (SL) between the individuals of the three stations. Values were tested for homogeneity (equality) and normal distribution with Shapiro-Wilks’ λ tests, respectively. Differences in the shape of the left and right otoliths contour from individuals at the three stations were analyzed with non-parametric generalized Discriminant Function Analysis (DFA). The DFA was performed using the normalized elliptical Fourier descriptors coefficients (65 coefficients per otolith) to illustrate the similarities and differences between individuals at the same station and/or across all stations. The objective of the DFA is to check the integrity of pre-defined groups of individuals belonging to the given geographical station or population and the percentage of their correct classification by finding linear combinations of descriptors. This statistic is the ratio between intra-group variance and total variance and it provides an objective method for calculating the corrected percentage chance of agreement. The effects of station location on elliptical Fourier descriptors were first tested by Multivariate Analysis of Variance (MANOVA). The Fisher’s distance and its p-values were also calculated to characterize differences in the shape of the otolith within and between individuals at all stations. All these statistical analyses were performed using XLSTAT 2010.

Stock discrimination

Intra-population comparison: The variability of otolith shape was analyzed for each sampled species from the three stations: Cap Zbib (CZ); Zarzouna (Z) and Ghar El Melh (GM) (Table 3). The p-values of the Fisher distances test revealed a shape asymmetry within the individuals of Cap Zbib samples (p-value <0.05) and a symmetry within the individuals of Zarzouna and Ghar El Melh samples (p-value 0.34; p-value=0.83).

Table 3:Test du Lambda de Wilks (approximation de Rao).

Intra-population comparison

Shape variability within the same sides of otoliths: right-right and left-left between the three sampled areas’ individuals: Cap Zbib (CZ), Zarzouna (Z) and Ghar El Melh (GM) (Table 4) confirmed, with p-values of Fisher distances, that no significant difference existed between Cap Zbib and Zarzouna samples (CZL-ZL; CZR -ZR). In addition, a shape symmetry was observed between Ghar El Melh and Zarzouna samples with (p=0.06; p=0.6). Additionally, no significant difference was identified between the same sides of the otolith of fishes from Cap Zbib and Ghar El Melh station. The DFA confirmed that fish from the three samples were discriminated against by the two axes F1 and F2 (Figure 3). The asymmetry between the right and left sides of S. maena species was expressed by a positive DFA axis 1 for the left sides and a negative DFA for most of the right sides, respectively. These factors together explain 59.12% of changes in shape symmetry on the DFA axes 1 and 2, both supporting a non-significant effect on this variability.

Table 4:P values of file distances built on an intra and inter populational comparison of otoliths between samples.

Figure 3:DFA depicting association between shape variability and sampling sites. Eigen values of the first two axes are indicated by 1 and 2. (R) Right sides of the Sagitta otolith of S. maena, (L) left sides in Cap Zbib (CZ), Zarzouna (Z) and Ghar El Melh (GM).

Stock discrimination

In this study, the otoliths from S. maena provide a basis for qualitative and quantitative otolith morphology analyses of this species. Our sampling was restricted to adult fish to avoid the sexual maturity effect, which can modify the outline contour of otoliths [8]. Actually, the complexity of the otolith outline increases with the ontogenetic stage of the fish. To limit this effect, sampling can be restricted to a specific life stage and/or to a narrow length range. If these factors are not taken into account, the results of otolith shapebased stock discrimination might be biased. In order to obtain more credible results, all the analyses in this study were carried out on adults of 250-265mm total length within a limited size range. In this case; all individuals were caught by artisanal fishing gear. These findings may require additional independent surveys to evidence geographic and environmental physicochemical parameters between marine stations. The discriminator function analysis showed no differences between the three stocks of S. maena when the same sides (right-right/left-left) of otoliths were compared (p<0.05). The results of the intra-population variation indicated the existence of an asymmetry between (Right/Left) otoliths within the stock of Cap Zbib. In addition, symmetry was detected between the otoliths of Zarzouna and Ghar El Melh stock.

Fish otolith shape from different geographical origins is affected by both abiotic environmental parameters, for example, temperature and salinity as well as biotic ones, such as prey availability. Besides, it is dependent on individual genotypes [8,27,29]. Consequently, a combination of both environmental and genetic variation generates the morphological differences in otolith shape that may allow the discrimination of stock units. However, the factors that influence the shape are not fully understood and have not been investigated deeply yet. A recent study showed that the ontogenetic trajectory of otolith shape could be affected by environmental disturbance during the early life stage [29]. Other studies have attributed shape differences to fish length [30], age [31], year class [11], sexual maturity [8], and sexual dimorphism [11]. In our case, the otolith morphological similarity between the samples of the three marine stations of Cap Zebib, Zarzouna and Ghar El Melh may be due to the resemblance of the environmental quality (temperature, movements of water masses, depth, etc.) of the studied stations [32-35].

Otolith shape analysis revealed no significant morphological differences among Spicara maena from Cap Zebib, Zarzouna, and Ghar El Melh, suggesting the presence of a single stock in the studied area. The observed similarity in otolith morphology is likely related to homogeneous environmental conditions and shared circulation patterns in the Mediterranean Sea [36-39]. Although otolithbased approaches provide valuable insights into stock structure, the results should be interpreted cautiously due to spatial and methodological limitations. Future studies integrating genetic analyses, otolith microchemistry, and broader spatial-temporal sampling are recommended to confirm population connectivity and support sustainable fisheries management.

At the end of this work, we would like to thank mainly the heads of the fishing districts of the northern region of Tunisia as well as Sabri JAZIRI and the fishermen for their cooperative efforts. We also appreciate the contribution of the ISPAB technicians to the laboratory work. On behalf of all authors, the corresponding author states that there is no conflict of interest

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