{"paper_id":"21937617-1242-4eef-a705-4e7ce0945b72","body_text":"Evaluation of otolith shape as an approach to stock discrimination of Mugil cephalus (Linnaeus, 1758) in the lagoon environments of Benin | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of otolith shape as an approach to stock discrimination of Mugil cephalus (Linnaeus, 1758) in the lagoon environments of Benin Houeto Madel Floriane Adjibayo, Andrialovanirina Nicolas, Mejri Marwa, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4219582/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study explores the ecological diversity of otoliths in Mugil cephalus by analysing data from 190 individuals collected at different sites, including the Porto Novo lagoon, the Cotonou lagoon and Lake Nokoué. The results revealed significant differences in otolith morphology, showing significant associations with the biological characteristics of the fish at each site. Analysis of the asymmetry between the right and left sides reveals distinctions between these two aspects. There is a significant structuring of stock units according to otolith shape, with marked differences between the different geographical sampling areas. The asymmetry percentages illustrate marked differences between the study sites, suggesting variations in the impact of environmental factors on otolith morphology. The higher asymmetry percentages observed in the Porto-Novo lagoon and the Cotonou lagoon indicate a different morphological response compared to Lake Nokoué, which could be attributable to distinct environmental conditions and specific selective pressures. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction West Africa is subject to the effects of climate change, making coastal areas particularly vulnerable to erosion (Niasse et al., 2004 ). The effects of climate change can have significant consequences for the biodiversity, functioning of these ecosystems (Munang et al., 2010), and consequently for fisheries.Today, fisheries are a source of local and a source of wealth for many developing countries. Fishery resources are a source of nutrients for the population. The importance of this activity no longer needs to be demonstrated, but this implies good management of fishery resources. Sustainable management requires knowledge of the life cycle of species, the dynamics of their populations and their ecosystems (Begg et al., 1998 ). In recent years, fisheries management has been based on the analysis of small white fragments called 'otoliths' found in the heads of teleost fish, which are a reliable and inexpensive tool for this study. These otoliths are used as a means of understanding the characteristics of life history through time (Monteiro et al., 2005 ; Tuset et al., 2003b ). The shape is conditioned by environmental conditions and results from the dorso-ventral to antero-posterior axis on the one hand, and the change in the area between the rostrum and the antirostrum due to the thermal factor on the other (Mahé et al., 2019 ). The progression of the shape of the otolith is associated with the morphology of the fish. This shape can be influenced by the development process of the species, the genetic process and also the environment (Mahé et al., 2019 ; Mille et al., 2015 ; Vignon, 2012 ). Fish living in different environmental conditions can therefore show disparities in otolith shape, and these differences can be characterised statistically. Otolith morphology is currently used as a complementary method for discriminating between fish stocks (Hussy et al., 2016; Ibanez et al., 2017 ). Shape variation is used to show distinctive characteristics of populations (intra- or inter-population) of living fish in different geographical areas or within and between estuaries (Chang et al., 2013) and even interspecifics (Mahé et al., 2019 ). This analytical method, among many others, is now used around the world and is being applied for the first time in Benin to Mugil cephalus , a commercial fish in the family Mugilidae. It is a catadromous fish species widely distributed in fresh, saline and hypo-saline waters of lagoons and shallow coastal marine waters less than 20 metres deep (FAO, 1990 ). It is one of the most important species in tropical and subtropical fisheries. The effects of salinity on the life history, growth, physiology and habitat selection of this fish have been discussed in various ways by Walsh et al ( 1989 , 1991 ); Lee and Menu ( 1981 ); Murashige et al, 1991 , Lee et al, 1992 , and Cardona, 2000 . The feeding habits of this species differ in time and space (Biol'e et al., 2019). Our study is focused on the morphological and morphometric characterisation of Mugil cephalus otoliths in three lagoon environments in Benin. The objective is to evaluate the relationship between fish size and otolith biometric parameters (length, width, surface area and perimeter). We will also assess otolith asymmetry, taking into account the different habitats of the Mugil cephalus . Otolith asymmetry will be tested and its variation between sampling sites will be studied. Material and methods Sampling site This comparative study focused on the waters of the Porto-Novo lagoon (Djassin), the Cotonou lagoon and Lake Nokoué (Calavi-Tokpa) (Fig. 1 ). The Porto-Novo lagoon, with an area of approximately 35 km2, is located in southeastern Benin between parallels 6° 25 and 6° 30 N and meridians 2° 30 and 2° 38 E. Lake Nokoué is located between parallels 6°20' and 6°30' North and meridians 2°20' and 2°35'. The lagoon of Porto-Novo is located in the department of Ouémé, between parallels 6°25'-6°30' North and meridians 2°30'-2°38. The Nokoué lagoon and the Porto - Novo lagoon are only the receptacles of the waters of the two rivers (Ouémé and Sô). These two environments communicate with each other and are replenished during low water periods, when the Atlantic tides are strong. On the other hand, they are very brackish during a long period of 4 to 5 months in the year. As for the Cotonou lagoon, its northern latitude is 6°22 and 2°25'60\" E. Sampling Mugil cephalus samples were collected during the months of January, March and May during the 2022 year. These samples came from three stations belonging to the Porto-Novo lagoon, Lake Nokoué and the Cotonou lagoon. Variation in otolith shape and size was examined in 190 individuals. The locations, sampling date and average standard length (nearest centimeter) of the fish are presented in Table 1 . In order to obtain a good differentiation of otolith size and shape, the samples have approximately similar lengths. Table 1 Sampling scheme Sampling site Total number of individuals length (cm) weight (g) N Max Min Mean ± SD Max Min Mean ± SD Lagoon of Porto Novo 64 22.60 11.10 17.59 ± 1.86 53.00 32.70 41.29 ± 3.98 Lagoon of Cotonou 60 25.70 12.80 17.20 ± 2.61 98.00 11.80 36.05 ± 16.70 Lake Nokoué 66 23.70 14.10 17.29 ± 2.03 115.90 22.90 47.32 ± 19.71 Extraction of the otolith and Image processing The present study was based on the sagittae (left and right). Extraction of this pair of otoliths (The left and right sagittae) was performed by cutting off the head and then removing the gills. The otoliths were collected with forceps, cleaned with distilled water, dried and preserved in Eppendorf tubes. The species name, area, and date of sampling were noted on a label adhered to the tube. Otoliths image acquisition was realized from a Canon powershot digital camera (12.1 Mega pixels) through a binocular microscope. Image processing of the whole otoliths was performed using photoshop CS6 image processing software. In order to compare the shapes of the left and right otoliths, a mirror image of the left otolith was used. Otoliths shape analysis The otolith outline was described using Fourier elliptic analysis (Lestrel, 2008) on each otolith. The contour was delimited and extracted after image pre-processing leading to a transformation of the original image into a binary image. The OpenCV library was then used to detect the otolith contours in the pre-processed image. This enabled the shape of the otolith to be represented as accurately as possible. The coordinates (x, y) of the main contour describing the shape of the contour were extracted (Andrialovanirina et al., 2023 ) . Elliptical Fourier analysis (Lestrel, 2008) was done on each otolith contour delimited and extracted after binarization of the image. For each otolith, the first 100 elliptical Fourier harmonics (H) were extracted and normalized with respect to the first harmonic and were therefore invariant to size, rotation and the starting point of the otolith contour description (Kuhl and Giardina,1982). To determine the number of harmonics required to reconstruct the otolith contour, the cumulative Fourier power (F) was calculated for each individual otolith as a measure of the accuracy of the contour reconstruction obtained with n harmonics): kn harmonics (i.e. the proportion of variance in the contour coordinates explained by the k $$F\\left(nk\\right)={\\sum }_{k=0}^{nk}\\frac{A{i}^{2}i+B{i}^{2}+{Ci}^{2}+{Di}^{2}}{2}$$ Where Ai, Bi, Ci and Di are the harmonic coefficients and nk is the total number of harmonics included. The value of nk was chosen so that F(nk) explains 99.99% of the variance in contour coordinates, i.e. it reconstructs the shape with 99.99% accuracy (Lestrel, 2008). In the second part of the study, ImageJ software was used (using a predefined scale of 1 millimeter) to determine otolith biometric parameters (length (Lo), width (Wo), area (Ao) and perimeter (Po)). Size parameters are measures directly related to otolith size, unlike shape indices, which are dimensionless measures and therefore independent of otolith size.The shape of the otolith relative to a geometric reference shape such as an ellipse for ellipticity (E), and a square for aspect ratio, was determined. They are simple to obtain, and the biological interpretation of the associated results is less complex than that of results obtained from multivariate data (Cadrin and Friedland, 1999; Stransky and MacLellan, 2005). Statistical analysis length-weight relations in fish are fish are considered to be allometric growth models of the type: Weight = K x length b The parameters of such a model are estimated by linear regression on data that have undergone a log-log transformation: Log(weight) = Log(K) + b x Log(length). Three types of descriptors were analyzed, including otolith size parameters (Length: 𝐿𝑜; Width: 𝑊𝑜; Perimeter: 𝑃𝑜; Area: 𝐴𝑜), shape indices (Ellipticity and aspect ratio), and EFDs. The analysis focused on the asymmetry between left and right otolith shapes, examining the impact of side on their morphology. To evaluate fluctuating asymmetry, the absolute value of the difference between the right and left sides for length, width, area and perimeter measurements was calculated. Then, the mean of the absolute value of the difference was calculated for each measurement. A Shapiro-Wilk normality test for each measurement was performed to assess the distribution of the data. Finally, a student’s t test to determine whether the mean differs significantly from zero was performed. the percentage of asymmetry using the mean of the absolute difference of otolith size parameters and the mean of the right side for each species was calculated. Finally, whisker box plots for each measure (length, width, area and perimeter) as a function of species and sampling site selected to visualize data distributions were produced. Principal component analysis (PCA) was applied to an otolith size matrix and the Elliptical Fourier Descriptor (EFD) matrix (Rohlf and Archie 1984). It enabled us to reduce the data size of EFD matrix while retaining as much information as possible, and to obtain a subset of the principal components. The selected principal components (PCs) can be used as shape descriptors of the otolith in our analysis (Mahé et al . 2016). Each principal component represents a specific shape feature. Then a matrix of the selected EFDs was created by organizing the selected elliptical Fourier descriptors into columns and the individual otoliths into rows (Mahé et al. 2016). Each cell of the matrix represents the value of the descriptor for a given otolith. For each pair of otoliths, the Euclidean distance was calculated. A mixed-effects model was used to test the effects of inner ear side, sampling site, sex, fish size and fish weight on otolith shape, but also the effect of sampling site, sex and side on size parameters (Length: 𝐿𝑜; Width: 𝑊𝑜; Perimeter: 𝑃𝑜; Area: 𝐴𝑜). Their interactions were also taken into account. Analysis of variance (ANOVA) was performed. using the mixed-effects model. This statistic measures the difference between the estimated variance of the model's random effects and the residual variance. For a better estimate of the divergences between samples, we performed multivariate analyses treating all traits simultaneously. Linear discriminant analysis (LDA) is a statistical analysis commonly used for classification and dimension reduction (Nasserallah, 2018). It is used to extract discriminant information from multivariate data for classification. Applied LDA is a classification algorithm that seeks to maximize the separation between classes using a linear combination of features. LDA using geographical positions to define the groups to be tested revealed principal components that significantly explained the variation in otolith shape. Canonical discriminant analysis (CDA) and mixed factorial discriminant analysis (MDFA) were then performed to assess the effect of gender, side and sampling site. All statistical tests were performed using the following packages in a python environment (Numpy (Boschetti, et Massaron, 2016), matplotlib (Boschetti, et Massaron, 2016), pyplot ,Scikit-learn (Boschetti, et Massaron, 2016), Pandas, mapply ,Plotnine, Plydata ,statsmodels (Boschetti, et Massaron, 2016), seaborn,scipy (Boschetti, et Massaron, 2016) and R statistical environment (Reichenbacher et Reichard, 2015): 'nlme' (Pinheiro et al., 2016 ), 'Effects' (Fox, 2003), 'Vegan' (Oksanen et al., 2013 ), 'SP' (Bivand et al., 2013 ), 'ggplot2' (Wickham, 2016), 'RGEOS' (Bivand et al., 2013 ), 'MASS' (Venables &Ripley, 2002 ) and 'RRCOV' (Todorov & Filzmoser, 2009 ). statistical environment python (pandas as pd, numpy as np, matplotlib.pyplot, seaborn, scipy). . Results Relations between Length and Weight of Fish The results show a significant variation in the association between fish length and weight from one site to another (Fig. 2 ). The slopes obtained from the linear regression models for each site are 2.149 for the Cotonou Lagoon, 0.836 for the Porto-Novo Lagoon and 3.048 for Lake Nokoué. The results confirm that the total length of the fish is strongly associated with its weight in each of the sites studied. There is a significant relationship between the total length of the fish and its weight. The Porto-Novo Lagoon shows an exceptionally strong relationship, followed closely by Lake Nokoué, while the Cotonou Lagoon shows a significant but relatively weaker relationship. Relations between fish size and otolith morphometrics Regression analysis between otolith biometric parameters and total fish length (Supplementary Appendix Table S2 ) revealed significant relationships in some study sites (Fig. 3 ), but not in others. At Lake Nokoué, significant correlations were observed between total fish length and otolith width, area and perimeter. This suggests that these biometric parameters can be used as reliable indicators of fish size in this environment. In the Porto-Novo lagoon, only the otolith area showed a weak and non-significant correlation with total fish length. In the Cotonou lagoon, none of the otolith biometric parameters showed a significant correlation with total fish length. Mixed-effect linear analysis The results of the analysis of variance (ANOVA) revealed that the effects of the site and side of the inner ear on the morphological characteristics of the otoliths (Table 2 ) varied, but these variations were not always statistically significant. The analyses indicated that for all the variables measured on the otoliths (length, width, area and perimeter), the differences recorded between the sides or sexes were not significant at a threshold of 5%. Table 2 Results of linear mixed model by each otolith morphological descriptor with the interaction between location and inner ear side and sex of Mugil cephalus. Parameters sum_sq Df F P-value Otolith Length Location:Side 1.082 2 1.618 0.20 Location:Sex 0.552 2 0.603 0.547 Otolith Width Location:Side 0.432 2 2.481 0.085 Location:Sex 0.234 2 1.189 0.305 Otolith Area Location:Side 0.321 2 2.446 0.088 Location:Sex 17.973 2 0.854 0.426 Otolith Perimeter Location:Side 32.179 2 2.446 0.089 Location:Sex 8.627 2 0.450 0,637 The Wilcoxon test is used to estimate otolith size asymmetries (Supplementary Appendix Table S 3). The results indicate the significance of the differences observed in the fluctuating asymmetry of otolith measurements between the right and left sides for each study site. For length, the difference in asymmetry between the right and left sides is significant for the Porto-Novo lagoon. However, for Lake Nokoué, although the p-value is slightly greater than 0.05, it indicates a tendency towards a significant difference between the right and left sides (Fig. 4 ). On the other hand, for the Cotonou lagoon, the difference in asymmetry is not statistically significant (p > 0.05). For the width, surface and perimeter of the otoliths, significant differences were observed between the right and left sides for all the study sites, with p values < 0.05. Analysis of variations in otolith characteristics Percentage average asymmetry of biometric parameters Analysis of the percentages of asymmetry reveals significant variations between the different study sites ( Supplementary Appendix Figure S5) . For otolith width, higher percentages of asymmetry were observed in the Porto-Novo lagoon (5.09%) and the Cotonou lagoon (4.81%) compared to Lake Nokoué (2.63%). Similarly, for otolith surface, the percentages of asymmetry are higher in the Porto-Novo lagoon (10.65%) compared to the Cotonou lagoon (6.67%) and Lake Nokoué (4.25%), indicating significant variations in otolith surface asymmetry between these sites. For otolith perimeter, the Porto-Novo lagoon also showed the highest percentage of asymmetry (6.54%), followed by the Cotonou lagoon (3.34%) and Lake Nokoué (1.44%), again suggesting significant differences in perimeter asymmetry between these sites. Finally, with regard to otolith length, although the percentages of asymmetry are relatively low overall, the Porto-Novo lagoon shows the highest percentage (4.38%), followed by Lake Nokoué (1.91% ) and the Cotonou lagoon (1.36%). These results indicate that the Porto-Novo Lagoon appears to have the highest mean asymmetries for all measurements, closely followed by the Cotonou Lagoon, while the Nokoué Lake generally shows lower mean asymmetries. The Mantel correlation test results in a correlation of -0.80 with a p-value of 0.413. This correlation is not statistically significant, indicating that no clear association was detected between biometric parameters and geographical distance. This suggests that there is no apparent linear relationship between biometric characteristics and geographical distance in the data analyzed. The correlation map ( Supplementary Appendix Figure S 6) shows low to moderate correlations between temperature and otolith measurements. On the other hand, correlations between pH and otolith measurements are moderate to high. Finally, strong and negative correlations were found between salinity and otolith measurements. These results reveal significant relationships between otolith measurements and environmental variables, in particular pH and salinity, which appear to exert a significant influence on otolith morphology. Variation in otolith shape according to the physiological and/or geographical factors The effect of sampling location on otolith shape ((Fig. 7 ).was significant in the multivariate mixed effects model suggesting a variation in otolith shape that could be used to discriminate individuals from different stations. The sampling site was therefore used as an explanatory variable based on otolith shape. The effect of weight was significant with a p value corresponding to 0.04957 so the shape is different between small and large fish. The multivariate mixed effects model on the shape matrix 𝑆 showed that there was a significant difference between left and right otoliths (0.001***) considering the sampling sites and between individuals according to sex (0.001***). After the PCA on the Elliptical Descriptors of Fourier (EFD), the first two PC realized explain to 62% of the total variance of the EFD Stock units structure according to otolith shape analysis The stock structure was studied using both the right and left otoliths simultaneously. Figure 8 shows the difference in average otolith shape. The difference in shape according to the sampling geographical area between the Porto-Novo lagoon and the Cotonou lagoon was 26.58%. On the other hand, this difference is 18.48% between the Porto-Novo lagoon and Lake Nokoué. Finally, there is a difference of 13.51% for the Porto-Novo lagoon and Lake Nokoué. The shape of the otoliths of the Cotonou lagoon were closer to those of Lake Nokoué than to those of the Porto-Novo lagoon. Discussion In fisheries science, the relationship between fish length and weight provides crucial data on their relative well-being and growth patterns. The results showed allometric growth at all sites, with variation in the direction of growth (positive or negative) between sites. The Cotonou Lagoon and Lake Nokoué show positive allometric growth, while the Porto-Novo Lagoon presents negative allometric growth. Similar results were observed by (Lederoun et al.,2017). Fish populations can be studied in various habitats to correlate fish population characteristics with otolith morphology (Annabi et al, 2013 ; Santos et al, 2017 ; Vignon, 2018 ). Local and location-specific variations in the assessment of the relationship between otolith biometric parameters and total fish length have been observed. The differences observed between locations can be attributed to a combination of environmental, ecological and biological factors specific to each aquatic habitat. Similar results were observed in the research carried out by Zorica et al ( 2010 ) on S. pilchardus in the Adriatic Sea. Many studies have demonstrated variations in otolith size correlated with fish growth, as shown by studies such as Templeman and Squires ( 1956 ), Boehlert (1985), Mosegaard et al. (1988) (Campana, 1990 ). Fluctuating asymmetry was found in width, area and perimeter at all three locations, with the exception of length, where the difference in asymmetry between the right and left sides was significant only in the Porto-Novo lagoon. Franco et al ( 2002 ) explained that the fluctuating asymmetry of four bilateral traits, namely otolith length, area and diameter of Zosterisessor ophiocephalus (Pallas, 1814), was attributable to differences in environmental stress levels between three sites in the Venice lagoon. In Benin, Lake Nokoué and the Porto-Novo lagoon are both filled by freshwater from Sô, in particular Ouérné. The Cotonou lagoon is an artificial reservoir created to facilitate the connection between Lake Nokoué and the Atlantic Ocean (Lalèyè et al, 2003 ). According to the research work of (Lalèyè et al, 2003 ), the Porto Novo lagoon seems to be linked to the oceanographic characteristics of the study area. As for the Cotonou lagoon and Lake Nokoué, they are under the influence of erosion, pollution by metals and organic contaminants and the increase in human activities, leading to a profound modification of the environment and a change in biodiversity (Lalèyè et al, 2003 ). Chang et al, 2013 confirmed that the elemental composition of the otolith of Mugil cephalus can be affected by salinity, which differs between freshwater and seawater. Our results highlight the importance of environmental variables, in particular pH and salinity, in determining otolith morphology. This is confirmed by the results of studies indicating that differences in otolith shape between populations can be caused by certain biotic and abiotic factors, notably salinity (Martin and Thorrold, 2005), depth (Lombarte, 1992; Lombarte and Cruz, 2007) and temperature.(Reichenbacher and Reichard, 2015) and biological factors such as habitat use and diet (Hussy, 2008). The results of this study also revealed significant variation in otolith shape as a function of physiological and geographical factors. Such variation in otolith shape in Liza ramada (Risso, 1827) has been explained by genetic or environmental stress during the development of the species. The effect of sampling location on otolith shape, as demonstrated by the multivariate mixed-effects model, suggests that geography is an important factor in determining otolith morphology. This spatial variation can be attributed to a combination of site-specific environmental factors, such as salinity, water temperature and habitat quality, which can influence fish growth and development.Such results were found by Galley et al., 2006 which states that differences in otolith shape between stocks may be related to environmental conditions and genetic differentiation .Vignon ( 2012 ) found that local environmental conditions cause significant variation in otolith shape. The results confirm that the variation in otolith shapes of Mugil cephalus is associated with the different geographical regions of the species. This is very similar to the results reported by other studies that have used the same analysis to discriminate stocks and have obtained satisfactory results, in particular the study on the discrimination of fish populations in the Atlantic and Mediterranean seas (Messaoud et al., 2011 ; Jemaa et al., 2015 b; Neves et al., 2021 , Houeto et al., 2023) by analysing otolith shapes. Declarations Acknowledgments: I would like to express my sincere gratitude to Dr Kakpo Césaire, CEO of K-POLYGONE multinational, for the financial support you provided for my research work. Your interest and encouragement were essential elements that enriched this experience. Ethical approval The Laboratory of Ecology, Biology and Physiology of Aquatic Organisms and the Laboratory of Biodiversity, Biotechnology and Climate Change of the Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia, have approved this research. In addition, all procedures in this study were carried out in accordance with the Guidelines for the Appropriate Conduct of Animal Experiments issued by the University of Tunis El Manar, Tunis, Tunisia (No. 1474 certified on August 14, 1995), as well as all applicable international, national and/or institutional guidelines for the care and use of animals in research. Funding not applicable Availability of data and material Otoliths, otolith images, Excel spreadsheet and python codes used Author Contribution HF, MT ,KM ont rédigé le texte principal du manuscritNA, SM statistique et figuresTous les auteurs ont révisé le manuscrit. References Adjibayo Houeto MF, Mejri M, Bakkari W, Bouriga N, Chalh A, Shahin AAAB, Quignard J-P, Trabelsi M, Ben Faleh A (2024). Discriminant inter and intrapopulation variation in sagittal otolith shape and morphometry in Chelon ramada (Actinopterygii, Mugilidae) from the Boughrara and El Bibane lagoons in Tunisian waters. 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(1992) The effect of salinity on the induction of spawning and fertilization in the striped mullet, Mugil cephalus. Aquaculture, 102: 289-296. Lombarte, A. et Cruz, A. (2007). Otolith size trends in marine fish communities from different depth strata. J. Fish Biol, 71: 53–76. Martin, G.B. et Thorrold, S.R. (2005). Temperature and salinity effects on magnesium, manganese, and barium incorporation in otoliths of larval and early juvenile spot Leiostomus xanthurus. Mar. Ecol. Prog. Ser, 293: 223–232. Mahé, K., Gourtay, C., BledDefruit, G., Chantre, C., de Pontual, H., Amara, R., et al. (2019). Do environmental conditions (temperature and food composition) affect otolith shape during fish early-juvenile phase? An experimental approach applied to European Seabass (Dicentrarchus labrax). J. Exp. Mar. Biol. Ecol. 521: 151239 Messaoud, H.; Bouriga, N.; Daly Yahia, M.N.; Boumaiza, M.; Faure, E.; Quignard, J.P. and Trabelsi, M. (2011). Discrimination de trois populations d’anchois du genre Engraulis (Clupeiforme, Engraulidae) des côtes Tunisiennes par analyse de forme des otolithes. Bulletin de l'Institut National des Sciences et Technologies de la Mer. 38. Mille, T., Mahé, K., Villanueva, C.M., de Pontual, H., Ernande, B. (2015). Sagittal otolith morphogenesis asymmetry in marine fishes. J. Fish Biol., 87: 646-663. Monteiro, L.R., Di Beneditto, A.P.M., Guillermo, L.H., Rivera, L.A. (2005). Allometric changes and shape differentiation of sagitta otoliths in sciaenid fishes. Fish. Res, 74: 288–299. Niasse, M., Afouda, A., Amani. A. (2004). Réduire la vulnérabilité de l'Afrique de l'ouest aux impacts du climat sur les ressources en eau, les zones humides et la désertification : Eléments de stratégie régionale de préparation et d'adaptation. UICN, Gland, Suisse et Cambidge, Royaume-uni. Murashige R., Bass P., Wallace L., Molnar A., Eastham B., Sato V., Tamaru C., Lee C. S. (1991). The effect of salinity on the survival and growth of striped mullet (Mugil cephalus) larvae in the hatchery. Aquaculture, 96(3-4): 249-254. Neves, J.; Silva, A.A.; Moreno, A.; Veríssimo, A.; Santos, A.M. and Garrido, S. (2021). Population structure of the European sardine Sardina pilchardus from Atlantic and Mediterranean waters based on otolith shape analysis. Fish. Res., 243. Oksanen, J., Blanchet, F.G., Kindt, R., Legendre, P., Minchin, P.R., O'Hara, R.B. et al. (2013). Vegan: Community Ecology Package. R package version 2.0–10. 292. Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. 2016. nlme: Linear and Nonlinear Mixed 687 Effects Models. R package version 3.1-128 Reichenbacher, B. et Reichard, M. (2015). Otoliths of five extant species of the annual killifish Nothobranchius from the East African Savannah. PLoS One, 10 (4): e0124984. Santos, R.S., Azevedo, M.C.C., Albuquerque, C.Q., Araújo, F.G. (2017). Different sagitta otolith morphotypes for the whitemouth croaker Micropogonias furnieri in the Southwestern Atlantic coast. Fish. Res. 195, 222–229. Templeman, W., Squires, H.J. (1956). Relationship of otolith lengths and weights in the haddock Melanogrammus rseglefinus (L.) to the rate of growth of the fish. J. Fish. Res. Board Can. 13: 467487. Todorov, V. and Filzmoser P. 2009. An Object-Oriented Framework for Robust 749 Multivariate Analysis. Journal of Statistical Software, 32(3): 1-47. Tuset, V.M., Lozano, I.J., Gonzalez, J.A., Pertusa, J.F., García-Diaz, M.M. (2003b). Shape indices to identify regional differences in otolith morphology of comber, Serranus cabrilla (L., 1758). J. Appl. Ichthyol. 19: 88–93. Vignon, M. (2018). Short-term stress for long-lasting otolith morphology – Brief embryological stress disturbance can reorient otolith ontogenetic trajectory. Can Jr Fisheries Aquat Sci, 75(10): 1713-1722 Venables, W. N., and Ripley, B. D. 2002. Modern Applied Statistics with S, 4th edn, 761 Springer, New York. 446 pp Vignon, M. (2012). Ontogenetic trajectories of otolith shape during shift in habitat use: interaction between otolith growth and environment. J. Exp. Mar. Biol. Ecol. 420: 26–32 Walsh W. A., Swanson C., Lee C.S., Banno J.E., Eda H. (1989). Oxygen consumption by eggs and larvae of striped mullet, Mugil cephalus, in relation to development, salinity and temperature. Journal of Fish Biology 35(3): 347–358. Walsh W. A., Swanson C., Lee C. S. (1991). Combined effects of temperature and salinity on embryonic development and hatching of striped mullet, Mugil cephalus . Aquaculture, 97(2-3): 281-289. Zorica, B.; Snovčić, G. and Čıkeś Keč, V. (2010). Preliminary data on the study of otolith morphology of five pelagic fish species from the Adriatic Sea (Croatia). Acta. Adriat., 5: 89–96. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-4219582\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":291136366,\"identity\":\"d9c05751-7336-4ed9-be80-ff7500a1c34f\",\"order_by\":0,\"name\":\"Houeto Madel Floriane Adjibayo\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBACAwglJ8PAwNj4AMji4SNKywEGYx6glmYQh4eNBC0MbBIgDkEt5uw9ho8/VBjw8Esfbqv8mmMnw8bA/PDRDTxaLHvOGBscOGPAI9mX2HZbdlsy0GFsxsY5+Bx2I8dM4mDbHx6DM4xttyW3MQO18LBJE9Bi/uNgmwFYS7HktnqitJgxwLQwftx2mAgtZ44VS5wB+aWHsVmacdtxHjZmQn453rzxQ0WFgRw/D/vDjz+3Vdvzszc/fIxPCwpg5gGTxCoHAcYfpKgeBaNgFIyCEQMAfy9DYuz/RogAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"University of Tunis El Manar\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Houeto\",\"middleName\":\"Madel Floriane\",\"lastName\":\"Adjibayo\",\"suffix\":\"\"},{\"id\":291136367,\"identity\":\"1c78f78f-5614-49eb-b86e-1aeb7181725c\",\"order_by\":1,\"name\":\"Andrialovanirina Nicolas\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"6IFREMER, Unit HMMN, Halieutic Resources Laboratory, Boulogne-sur-mer, France\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Andrialovanirina\",\"middleName\":\"\",\"lastName\":\"Nicolas\",\"suffix\":\"\"},{\"id\":291136368,\"identity\":\"0f63082a-c458-4888-af35-b0fc6456510a\",\"order_by\":2,\"name\":\"Mejri Marwa\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tunis El Manar\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mejri\",\"middleName\":\"\",\"lastName\":\"Marwa\",\"suffix\":\"\"},{\"id\":291136369,\"identity\":\"a68581c1-861f-4b3a-93b9-9194cdb7441f\",\"order_by\":3,\"name\":\"Tazarki Malek\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tunis El Manar\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Tazarki\",\"middleName\":\"\",\"lastName\":\"Malek\",\"suffix\":\"\"},{\"id\":291136370,\"identity\":\"1e7f014f-9f98-4543-b55a-40e66796470e\",\"order_by\":4,\"name\":\"Sounouvou Marius\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Université d'Abomey-Calavi\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sounouvou\",\"middleName\":\"\",\"lastName\":\"Marius\",\"suffix\":\"\"},{\"id\":291136371,\"identity\":\"2306fd85-26b0-48b9-87e1-0d03de7b654d\",\"order_by\":5,\"name\":\"Ben Ghorbel Meriem\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tunis El Manar\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ben\",\"middleName\":\"Ghorbel\",\"lastName\":\"Meriem\",\"suffix\":\"\"},{\"id\":291136372,\"identity\":\"4ccb830f-51b5-4a0e-b7ce-c2a78f19b3c3\",\"order_by\":6,\"name\":\"Dossou-Yovo Pierre\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Université d'Abomey-Calavi\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Dossou-Yovo\",\"middleName\":\"\",\"lastName\":\"Pierre\",\"suffix\":\"\"},{\"id\":291136373,\"identity\":\"41454a13-00f8-4917-bb3a-09ef54df6ee8\",\"order_by\":7,\"name\":\"Abdellah Chalh\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tunis El Manar\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Abdellah\",\"middleName\":\"\",\"lastName\":\"Chalh\",\"suffix\":\"\"},{\"id\":291136374,\"identity\":\"f009bc1c-78bb-4c28-b7a4-26e107394c5f\",\"order_by\":8,\"name\":\"Jean-Pierre Quignard\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Laboratoire d’Ichtyologie, Université Montpellier П, Montpellier, France\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jean-Pierre\",\"middleName\":\"\",\"lastName\":\"Quignard\",\"suffix\":\"\"},{\"id\":291136375,\"identity\":\"b49c37fa-1881-42b6-a7ec-fdef2284d7c7\",\"order_by\":9,\"name\":\"Trabelsi Monia\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tunis El Manar\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Trabelsi\",\"middleName\":\"\",\"lastName\":\"Monia\",\"suffix\":\"\"},{\"id\":291136376,\"identity\":\"cf9c1e3f-cbf8-4c28-b1e0-4e8c4a2cf9d5\",\"order_by\":10,\"name\":\"Mahé Kélig\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"6IFREMER, Unit HMMN, Halieutic Resources Laboratory, Boulogne-sur-mer, France\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mahé\",\"middleName\":\"\",\"lastName\":\"Kélig\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-04-04 19:44:14\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4219582/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4219582/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":55061669,\"identity\":\"bce77fc6-2766-402c-b81a-1663b31f9b53\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 02:50:56\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":123752,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eMap showing sampling stations\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4219582/v1/95b167e149a875f0af01c143.png\"},{\"id\":55061650,\"identity\":\"fc707533-a5ad-44d1-b2c7-f10b6f8999c4\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 02:50:49\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":68690,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eRegression showing the correlation between a fish total length (TL) and weight (W).\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4219582/v1/afdd8047eb0a7fd064f42c56.png\"},{\"id\":55061696,\"identity\":\"acd84c97-0e42-4690-945e-6186ebabc7cb\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 02:51:00\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":338022,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eRegression showing the correlation between fish size and otolith morphometrics (A:Area ; B: Length; C:Width ; D: Perimeter).\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4219582/v1/4fb1fc5c26f159891a358619.png\"},{\"id\":55061652,\"identity\":\"40341d17-fe1d-4fa5-ab19-81bb1d9740a4\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 02:50:50\",\"extension\":\"jpeg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":228294,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eDifference between the mean shapes of the reconstructed left and right otoliths at each station. (A: Porto-Novo Lagoon, B: Lake Nokoue, C: Cotonou Lagoon).\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4219582/v1/c61da0e2300f1faf29f64920.jpeg\"},{\"id\":55061649,\"identity\":\"91fc6cab-4104-4756-97bc-0add4921b7b0\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 02:50:45\",\"extension\":\"jpeg\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":477591,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eFigure 7:\\u003c/strong\\u003e Difference between the mean shapes of the reconstructed otoliths between the identified stock units: Lake Nokoué (red colour; Left: solid line, Right: dotted line), Cotonou Lagoon (blue colour; Left: solid line, Right: dotted line), Porto-Novo Lagoon (Left: solid line, Right: dotted line)\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4219582/v1/d4e93e7208f8448b6941b75f.jpeg\"},{\"id\":55061642,\"identity\":\"bd7a6381-8cba-49f9-9bec-aab92a4a832b\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 02:50:41\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":54921,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eFigure 8:\\u003c/strong\\u003e Difference between the average shapes of the reconstructed otoliths between the three sampling sites: Lagoon of Porto-Novo (solid line), Lagoon of Cotonou (dotted red line), and Lake Nokoué (dotted green line)\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4219582/v1/fa56ab1e272583bb83e339c2.png\"},{\"id\":56399601,\"identity\":\"7eb7dd2b-a764-4d6c-9838-3bd8486a9917\",\"added_by\":\"auto\",\"created_at\":\"2024-05-13 16:11:29\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1507392,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4219582/v1/fb1e0a10-1d61-4e0e-81fc-b765d06f186f.pdf\"},{\"id\":55061646,\"identity\":\"1c05bf2b-5fc5-4dbc-b48d-c1de239e23c6\",\"added_by\":\"auto\",\"created_at\":\"2024-04-22 02:50:42\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":95086,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"supplementary.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4219582/v1/410a0c0eb1d3a1a81089c416.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Evaluation of otolith shape as an approach to stock discrimination of Mugil cephalus (Linnaeus, 1758) in the lagoon environments of Benin\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eWest Africa is subject to the effects of climate change, making coastal areas particularly vulnerable to erosion (Niasse et al., \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e). The effects of climate change can have significant consequences for the biodiversity, functioning of these ecosystems (Munang et al., 2010), and consequently for fisheries.Today, fisheries are a source of local and a source of wealth for many developing countries. Fishery resources are a source of nutrients for the population. The importance of this activity no longer needs to be demonstrated, but this implies good management of fishery resources. Sustainable management requires knowledge of the life cycle of species, the dynamics of their populations and their ecosystems (Begg et al., \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e1998\\u003c/span\\u003e). In recent years, fisheries management has been based on the analysis of small white fragments called 'otoliths' found in the heads of teleost fish, which are a reliable and inexpensive tool for this study.\\u003c/p\\u003e \\u003cp\\u003eThese otoliths are used as a means of understanding the characteristics of life history through time (Monteiro et al., \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e2005\\u003c/span\\u003e; Tuset et al., \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e2003b\\u003c/span\\u003e). The shape is conditioned by environmental conditions and results from the dorso-ventral to antero-posterior axis on the one hand, and the change in the area between the rostrum and the antirostrum due to the thermal factor on the other (Mah\\u0026eacute; et al., \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). The progression of the shape of the otolith is associated with the morphology of the fish. This shape can be influenced by the development process of the species, the genetic process and also the environment (Mah\\u0026eacute; et al., \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e; Mille et al., \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e; Vignon, \\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e). Fish living in different environmental conditions can therefore show disparities in otolith shape, and these differences can be characterised statistically. Otolith morphology is currently used as a complementary method for discriminating between fish stocks (Hussy et al., 2016; Ibanez et al., \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eShape variation is used to show distinctive characteristics of populations (intra- or inter-population) of living fish in different geographical areas or within and between estuaries (Chang et al., 2013) and even interspecifics (Mah\\u0026eacute; et al., \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThis analytical method, among many others, is now used around the world and is being applied for the first time in Benin to \\u003cem\\u003eMugil cephalus\\u003c/em\\u003e, a commercial fish in the family Mugilidae. It is a catadromous fish species widely distributed in fresh, saline and hypo-saline waters of lagoons and shallow coastal marine waters less than 20 metres deep (FAO, \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e1990\\u003c/span\\u003e). It is one of the most important species in tropical and subtropical fisheries. The effects of salinity on the life history, growth, physiology and habitat selection of this fish have been discussed in various ways by Walsh et al (\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e1989\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e1991\\u003c/span\\u003e); Lee and Menu (\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e1981\\u003c/span\\u003e); Murashige et al, \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e1991\\u003c/span\\u003e, Lee et al, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e1992\\u003c/span\\u003e, and Cardona, \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2000\\u003c/span\\u003e. The feeding habits of this species differ in time and space (Biol'e et al., 2019).\\u003c/p\\u003e \\u003cp\\u003eOur study is focused on the morphological and morphometric characterisation of \\u003cem\\u003eMugil cephalus\\u003c/em\\u003e otoliths in three lagoon environments in Benin. The objective is to evaluate the relationship between fish size and otolith biometric parameters (length, width, surface area and perimeter). We will also assess otolith asymmetry, taking into account the different habitats of the \\u003cem\\u003eMugil cephalus\\u003c/em\\u003e. Otolith asymmetry will be tested and its variation between sampling sites will be studied.\\u003c/p\\u003e\"},{\"header\":\"Material and methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSampling site\\u003c/h2\\u003e \\u003cp\\u003eThis comparative study focused on the waters of the Porto-Novo lagoon (Djassin), the Cotonou lagoon and Lake Nokou\\u0026eacute; (Calavi-Tokpa) (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e). The Porto-Novo lagoon, with an area of approximately 35 km2, is located in southeastern Benin between parallels 6\\u0026deg; 25 and 6\\u0026deg; 30 N and meridians 2\\u0026deg; 30 and 2\\u0026deg; 38 E. Lake Nokou\\u0026eacute; is located between parallels 6\\u0026deg;20' and 6\\u0026deg;30' North and meridians 2\\u0026deg;20' and 2\\u0026deg;35'. The lagoon of Porto-Novo is located in the department of Ou\\u0026eacute;m\\u0026eacute;, between parallels 6\\u0026deg;25'-6\\u0026deg;30' North and meridians 2\\u0026deg;30'-2\\u0026deg;38. The Nokou\\u0026eacute; lagoon and the Porto - Novo lagoon are only the receptacles of the waters of the two rivers (Ou\\u0026eacute;m\\u0026eacute; and S\\u0026ocirc;). These two environments communicate with each other and are replenished during low water periods, when the Atlantic tides are strong. On the other hand, they are very brackish during a long period of 4 to 5 months in the year. As for the Cotonou lagoon, its northern latitude is 6\\u0026deg;22 and 2\\u0026deg;25'60\\\" E.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSampling\\u003c/h2\\u003e \\u003cp\\u003e \\u003cem\\u003eMugil cephalus\\u003c/em\\u003e samples were collected during the months of January, March and May during the 2022 year. These samples came from three stations belonging to the Porto-Novo lagoon, Lake Nokou\\u0026eacute; and the Cotonou lagoon. Variation in otolith shape and size was examined in 190 individuals. The locations, sampling date and average standard length (nearest centimeter) of the fish are presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. In order to obtain a good differentiation of otolith size and shape, the samples have approximately similar lengths.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eSampling scheme\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eSampling site\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTotal number of individuals\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c5\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003elength (cm)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c8\\\" namest=\\\"c6\\\"\\u003e \\u003cp\\u003eweight (g)\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eN\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMax\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eMin\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eMean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eMax\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eMin\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eMean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLagoon of Porto Novo\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e64\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e22.60\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e11.10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e17.59\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.86\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e53.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e32.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e41.29\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;3.98\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLagoon of Cotonou\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e60\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e25.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e12.80\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e17.20\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e98.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e11.80\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e36.05\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;16.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eLake Nokou\\u0026eacute;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e66\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e23.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e14.10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e17.29\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;2.03\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e115.90\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e22.90\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\"\\u0026plusmn;\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e47.32\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;19.71\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eExtraction of the otolith and Image processing\\u003c/h2\\u003e \\u003cp\\u003eThe present study was based on the \\u003cem\\u003esagittae\\u003c/em\\u003e (left and right). Extraction of this pair of otoliths (The left and right \\u003cem\\u003esagittae)\\u003c/em\\u003e was performed by cutting off the head and then removing the gills. The otoliths were collected with forceps, cleaned with distilled water, dried and preserved in Eppendorf tubes. The species name, area, and date of sampling were noted on a label adhered to the tube. Otoliths image acquisition was realized from a Canon powershot digital camera (12.1 Mega pixels) through a binocular microscope. Image processing of the whole otoliths was performed using photoshop CS6 image processing software. In order to compare the shapes of the left and right otoliths, a mirror image of the left otolith was used.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eOtoliths shape analysis\\u003c/h2\\u003e \\u003cp\\u003eThe otolith outline was described using Fourier elliptic analysis (Lestrel, 2008) on each otolith. The contour was delimited and extracted after image pre-processing leading to a transformation of the original image into a binary image. The OpenCV library was then used to detect the otolith contours in the pre-processed image. This enabled the shape of the otolith to be represented as accurately as possible. The coordinates (x, y) of the main contour describing the shape of the contour were extracted (Andrialovanirina et al., 2023\\u003cb\\u003e)\\u003c/b\\u003e. Elliptical Fourier analysis (Lestrel, 2008) was done on each otolith contour delimited and extracted after binarization of the image. For each otolith, the first 100 elliptical Fourier harmonics (H) were extracted and normalized with respect to the first harmonic and were therefore invariant to size, rotation and the starting point of the otolith contour description (Kuhl and Giardina,1982). To determine the number of harmonics required to reconstruct the otolith contour, the cumulative Fourier power (F) was calculated for each individual otolith as a measure of the accuracy of the contour reconstruction obtained with n harmonics): kn harmonics (i.e. the proportion of variance in the contour coordinates explained by the k\\u003cdiv id=\\\"Equa\\\" class=\\\"Equation\\\"\\u003e\\u003cdiv format=\\\"TEX\\\" class=\\\"mathdisplay\\\" id=\\\"FileID_Equa\\\" name=\\\"EquationSource\\\"\\u003e\\n$$F\\\\left(nk\\\\right)={\\\\sum }_{k=0}^{nk}\\\\frac{A{i}^{2}i+B{i}^{2}+{Ci}^{2}+{Di}^{2}}{2}$$\\u003c/div\\u003e\\u003c/div\\u003e\\u003c/p\\u003e \\u003cp\\u003eWhere Ai, Bi, Ci and Di are the harmonic coefficients and nk is the total number of harmonics included.\\u003c/p\\u003e \\u003cp\\u003eThe value of nk was chosen so that \\u003cem\\u003eF(nk)\\u003c/em\\u003e explains 99.99% of the variance in contour coordinates, i.e. it reconstructs the shape with 99.99% accuracy (Lestrel, 2008).\\u003c/p\\u003e \\u003cp\\u003eIn the second part of the study, ImageJ software was used (using a predefined scale of 1 millimeter) to determine otolith biometric parameters (length (Lo), width (Wo), area (Ao) and perimeter (Po)).\\u003c/p\\u003e \\u003cp\\u003eSize parameters are measures directly related to otolith size, unlike shape indices, which are dimensionless measures and therefore independent of otolith size.The shape of the otolith relative to a geometric reference shape such as an ellipse for ellipticity (E), and a square for aspect ratio, was determined. They are simple to obtain, and the biological interpretation of the associated results is less complex than that of results obtained from multivariate data (Cadrin and Friedland, 1999; Stransky and MacLellan, 2005).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical analysis\\u003c/h2\\u003e \\u003cp\\u003elength-weight relations in fish are fish are considered to be allometric growth models of the type:\\u003c/p\\u003e \\u003cp\\u003eWeight\\u0026thinsp;=\\u0026thinsp;K x length\\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003eThe parameters of such a model are estimated by linear regression on data that have undergone a log-log transformation:\\u003c/p\\u003e \\u003cp\\u003eLog(weight)\\u0026thinsp;=\\u0026thinsp;Log(K)\\u0026thinsp;+\\u0026thinsp;b x Log(length).\\u003c/p\\u003e \\u003cp\\u003eThree types of descriptors were analyzed, including otolith size parameters (Length: \\u0026#119871;\\u0026#119900;; Width: \\u0026#119882;\\u0026#119900;; Perimeter: \\u0026#119875;\\u0026#119900;; Area: \\u0026#119860;\\u0026#119900;), shape indices (Ellipticity and aspect ratio), and EFDs.\\u003c/p\\u003e \\u003cp\\u003eThe analysis focused on the asymmetry between left and right otolith shapes, examining the impact of side on their morphology. To evaluate fluctuating asymmetry, the absolute value of the difference between the right and left sides for length, width, area and perimeter measurements was calculated. Then, the mean of the absolute value of the difference was calculated for each measurement.\\u003c/p\\u003e \\u003cp\\u003eA Shapiro-Wilk normality test for each measurement was performed to assess the distribution of the data. Finally, a student\\u0026rsquo;s t test to determine whether the mean differs significantly from zero was performed. the percentage of asymmetry using the mean of the absolute difference of otolith size parameters and the mean of the right side for each species was calculated.\\u003c/p\\u003e \\u003cp\\u003eFinally, whisker box plots for each measure (length, width, area and perimeter) as a function of species and sampling site selected to visualize data distributions were produced.\\u003c/p\\u003e \\u003cp\\u003ePrincipal component analysis (PCA) was applied to an otolith size matrix and the Elliptical Fourier Descriptor (EFD) matrix (Rohlf and Archie 1984). It enabled us to reduce the data size of EFD matrix while retaining as much information as possible, and to obtain a subset of the principal components. The selected principal components (PCs) can be used as shape descriptors of the otolith in our analysis (Mah\\u0026eacute; \\u003cem\\u003eet al\\u003c/em\\u003e. 2016). Each principal component represents a specific shape feature. Then a matrix of the selected EFDs was created by organizing the selected elliptical Fourier descriptors into columns and the individual otoliths into rows (Mah\\u0026eacute; et al. 2016). Each cell of the matrix represents the value of the descriptor for a given otolith. For each pair of otoliths, the Euclidean distance was calculated.\\u003c/p\\u003e \\u003cp\\u003eA mixed-effects model was used to test the effects of inner ear side, sampling site, sex, fish size and fish weight on otolith shape, but also the effect of sampling site, sex and side on size parameters (Length: \\u0026#119871;\\u0026#119900;; Width: \\u0026#119882;\\u0026#119900;; Perimeter: \\u0026#119875;\\u0026#119900;; Area: \\u0026#119860;\\u0026#119900;). Their interactions were also taken into account. Analysis of variance (ANOVA) was performed. using the mixed-effects model. This statistic measures the difference between the estimated variance of the model's random effects and the residual variance.\\u003c/p\\u003e \\u003cp\\u003eFor a better estimate of the divergences between samples, we performed multivariate analyses treating all traits simultaneously. Linear discriminant analysis (LDA) is a statistical analysis commonly used for classification and dimension reduction (Nasserallah, 2018). It is used to extract discriminant information from multivariate data for classification.\\u003c/p\\u003e \\u003cp\\u003eApplied LDA is a classification algorithm that seeks to maximize the separation between classes using a linear combination of features.\\u003c/p\\u003e \\u003cp\\u003eLDA using geographical positions to define the groups to be tested revealed principal components that significantly explained the variation in otolith shape. Canonical discriminant analysis (CDA) and mixed factorial discriminant analysis (MDFA) were then performed to assess the effect of gender, side and sampling site.\\u003c/p\\u003e \\u003cp\\u003eAll statistical tests were performed using the following packages in a python environment (Numpy (Boschetti, et Massaron, 2016), matplotlib (Boschetti, et Massaron, 2016), pyplot ,Scikit-learn (Boschetti, et Massaron, 2016), Pandas, mapply ,Plotnine, Plydata ,statsmodels (Boschetti, et Massaron, 2016), seaborn,scipy (Boschetti, et Massaron, 2016) and R statistical environment (Reichenbacher et Reichard, 2015): 'nlme' (Pinheiro et al., \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e), 'Effects' (Fox, 2003), 'Vegan' (Oksanen et al., \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e), 'SP' (Bivand et al., \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e), 'ggplot2' (Wickham, 2016), 'RGEOS' (Bivand et al., \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e), 'MASS' (Venables \\u0026amp;Ripley, \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e2002\\u003c/span\\u003e) and 'RRCOV' (Todorov \\u0026amp; Filzmoser, \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e). statistical environment python (pandas as pd, numpy as np, matplotlib.pyplot, seaborn, scipy).\\u003c/p\\u003e \\u003cp\\u003e.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eRelations between Length and Weight of Fish\\u003c/h2\\u003e \\u003cp\\u003eThe results show a significant variation in the association between fish length and weight from one site to another (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). The slopes obtained from the linear regression models for each site are 2.149 for the Cotonou Lagoon, 0.836 for the Porto-Novo Lagoon and 3.048 for Lake Nokou\\u0026eacute;. The results confirm that the total length of the fish is strongly associated with its weight in each of the sites studied. There is a significant relationship between the total length of the fish and its weight. The Porto-Novo Lagoon shows an exceptionally strong relationship, followed closely by Lake Nokou\\u0026eacute;, while the Cotonou Lagoon shows a significant but relatively weaker relationship.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eRelations between fish size and otolith morphometrics\\u003c/h2\\u003e \\u003cp\\u003eRegression analysis between otolith biometric parameters and total fish length (Supplementary Appendix Table \\u003cspan refid=\\\"MOESM2\\\" class=\\\"InternalRef\\\"\\u003eS2\\u003c/span\\u003e) revealed significant relationships in some study sites (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e), but not in others. At Lake Nokou\\u0026eacute;, significant correlations were observed between total fish length and otolith width, area and perimeter. This suggests that these biometric parameters can be used as reliable indicators of fish size in this environment. In the Porto-Novo lagoon, only the otolith area showed a weak and non-significant correlation with total fish length. In the Cotonou lagoon, none of the otolith biometric parameters showed a significant correlation with total fish length.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eMixed-effect linear analysis\\u003c/h2\\u003e \\u003cp\\u003eThe results of the analysis of variance (ANOVA) revealed that the effects of the site and side of the inner ear on the morphological characteristics of the otoliths (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e) varied, but these variations were not always statistically significant. The analyses indicated that for all the variables measured on the otoliths (length, width, area and perimeter), the differences recorded between the sides or sexes were not significant at a threshold of 5%.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eResults of linear mixed model by each otolith morphological descriptor with the interaction between location and inner ear side and sex of \\u003cem\\u003eMugil cephalus.\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"6\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\"\\u003e \\u003cp\\u003eParameters\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003esum_sq\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eDf\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eF\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eP-value\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eOtolith Length\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eLocation:Side\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.082\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.618\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.20\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eLocation:Sex\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.552\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.603\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.547\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eOtolith Width\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eLocation:Side\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.432\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.481\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.085\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eLocation:Sex\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.234\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.189\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.305\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eOtolith Area\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eLocation:Side\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.321\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.446\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.088\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eLocation:Sex\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e17.973\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.854\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.426\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eOtolith Perimeter\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eLocation:Side\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e32.179\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.446\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.089\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eLocation:Sex\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8.627\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.450\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0,637\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe Wilcoxon test is used to estimate otolith size asymmetries (Supplementary Appendix Table S 3). The results indicate the significance of the differences observed in the fluctuating asymmetry of otolith measurements between the right and left sides for each study site. For length, the difference in asymmetry between the right and left sides is significant for the Porto-Novo lagoon. However, for Lake Nokou\\u0026eacute;, although the p-value is slightly greater than 0.05, it indicates a tendency towards a significant difference between the right and left sides (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). On the other hand, for the Cotonou lagoon, the difference in asymmetry is not statistically significant (p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05). For the width, surface and perimeter of the otoliths, significant differences were observed between the right and left sides for all the study sites, with p values\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eAnalysis of variations in otolith characteristics\\u003c/h2\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003ePercentage average asymmetry of biometric parameters\\u003c/h2\\u003e \\u003cp\\u003eAnalysis of the percentages of asymmetry reveals significant variations between the different study sites (\\u003cb\\u003eSupplementary Appendix Figure S5)\\u003c/b\\u003e. For otolith width, higher percentages of asymmetry were observed in the Porto-Novo lagoon (5.09%) and the Cotonou lagoon (4.81%) compared to Lake Nokou\\u0026eacute; (2.63%). Similarly, for otolith surface, the percentages of asymmetry are higher in the Porto-Novo lagoon (10.65%) compared to the Cotonou lagoon (6.67%) and Lake Nokou\\u0026eacute; (4.25%), indicating significant variations in otolith surface asymmetry between these sites. For otolith perimeter, the Porto-Novo lagoon also showed the highest percentage of asymmetry (6.54%), followed by the Cotonou lagoon (3.34%) and Lake Nokou\\u0026eacute; (1.44%), again suggesting significant differences in perimeter asymmetry between these sites. Finally, with regard to otolith length, although the percentages of asymmetry are relatively low overall, the Porto-Novo lagoon shows the highest percentage (4.38%), followed by Lake Nokou\\u0026eacute; (1.91% ) and the Cotonou lagoon (1.36%). These results indicate that the Porto-Novo Lagoon appears to have the highest mean asymmetries for all measurements, closely followed by the Cotonou Lagoon, while the Nokou\\u0026eacute; Lake generally shows lower mean asymmetries.\\u003c/p\\u003e \\u003cp\\u003eThe Mantel correlation test results in a correlation of -0.80 with a p-value of 0.413. This correlation is not statistically significant, indicating that no clear association was detected between biometric parameters and geographical distance. This suggests that there is no apparent linear relationship between biometric characteristics and geographical distance in the data analyzed.\\u003c/p\\u003e \\u003cp\\u003eThe correlation map (\\u003cb\\u003eSupplementary Appendix Figure S\\u003c/b\\u003e6) shows low to moderate correlations between temperature and otolith measurements. On the other hand, correlations between pH and otolith measurements are moderate to high. Finally, strong and negative correlations were found between salinity and otolith measurements. These results reveal significant relationships between otolith measurements and environmental variables, in particular pH and salinity, which appear to exert a significant influence on otolith morphology.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eVariation in otolith shape according to the physiological and/or geographical factors\\u003c/h2\\u003e \\u003cp\\u003eThe effect of sampling location on otolith shape ((Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e).was significant in the multivariate mixed effects model suggesting a variation in otolith shape that could be used to discriminate individuals from different stations. The sampling site was therefore used as an explanatory variable based on otolith shape. The effect of weight was significant with a p value corresponding to 0.04957 so the shape is different between small and large fish. The multivariate mixed effects model on the shape matrix \\u0026#119878; showed that there was a significant difference between left and right otoliths (0.001***) considering the sampling sites and between individuals according to sex (0.001***). After the PCA on the Elliptical Descriptors of Fourier (EFD), the first two PC realized explain to 62% of the total variance of the EFD\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStock units structure according to otolith shape analysis\\u003c/h2\\u003e \\u003cp\\u003eThe stock structure was studied using both the right and left otoliths simultaneously. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig8\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e shows the difference in average otolith shape. The difference in shape according to the sampling geographical area between the Porto-Novo lagoon and the Cotonou lagoon was 26.58%. On the other hand, this difference is 18.48% between the Porto-Novo lagoon and Lake Nokou\\u0026eacute;. Finally, there is a difference of 13.51% for the Porto-Novo lagoon and Lake Nokou\\u0026eacute;. The shape of the otoliths of the Cotonou lagoon were closer to those of Lake Nokou\\u0026eacute; than to those of the Porto-Novo lagoon.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eIn fisheries science, the relationship between fish length and weight provides crucial data on their relative well-being and growth patterns. The results showed allometric growth at all sites, with variation in the direction of growth (positive or negative) between sites. The Cotonou Lagoon and Lake Nokou\\u0026eacute; show positive allometric growth, while the Porto-Novo Lagoon presents negative allometric growth. Similar results were observed by (Lederoun et al.,2017). Fish populations can be studied in various habitats to correlate fish population characteristics with otolith morphology (Annabi et al, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e; Santos et al, \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e; Vignon, \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). Local and location-specific variations in the assessment of the relationship between otolith biometric parameters and total fish length have been observed. The differences observed between locations can be attributed to a combination of environmental, ecological and biological factors specific to each aquatic habitat. Similar results were observed in the research carried out by Zorica et al (\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e2010\\u003c/span\\u003e) on S. pilchardus in the Adriatic Sea. Many studies have demonstrated variations in otolith size correlated with fish growth, as shown by studies such as Templeman and Squires (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e1956\\u003c/span\\u003e), Boehlert (1985), Mosegaard et al. (1988) (Campana, \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e1990\\u003c/span\\u003e). Fluctuating asymmetry was found in width, area and perimeter at all three locations, with the exception of length, where the difference in asymmetry between the right and left sides was significant only in the Porto-Novo lagoon. Franco et al (\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2002\\u003c/span\\u003e) explained that the fluctuating asymmetry of four bilateral traits, namely otolith length, area and diameter of \\u003cem\\u003eZosterisessor ophiocephalus\\u003c/em\\u003e (Pallas, 1814), was attributable to differences in environmental stress levels between three sites in the Venice lagoon. In Benin, Lake Nokou\\u0026eacute; and the Porto-Novo lagoon are both filled by freshwater from S\\u0026ocirc;, in particular Ou\\u0026eacute;rn\\u0026eacute;. The Cotonou lagoon is an artificial reservoir created to facilitate the connection between Lake Nokou\\u0026eacute; and the Atlantic Ocean (Lal\\u0026egrave;y\\u0026egrave; et al, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e). According to the research work of (Lal\\u0026egrave;y\\u0026egrave; et al, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e), the Porto Novo lagoon seems to be linked to the oceanographic characteristics of the study area. As for the Cotonou lagoon and Lake Nokou\\u0026eacute;, they are under the influence of erosion, pollution by metals and organic contaminants and the increase in human activities, leading to a profound modification of the environment and a change in biodiversity (Lal\\u0026egrave;y\\u0026egrave; et al, \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e). Chang et al, 2013 confirmed that the elemental composition of the otolith of \\u003cem\\u003eMugil cephalus\\u003c/em\\u003e can be affected by salinity, which differs between freshwater and seawater. Our results highlight the importance of environmental variables, in particular pH and salinity, in determining otolith morphology. This is confirmed by the results of studies indicating that differences in otolith shape between populations can be caused by certain biotic and abiotic factors, notably salinity (Martin and Thorrold, 2005), depth (Lombarte, 1992; Lombarte and Cruz, 2007) and temperature.(Reichenbacher and Reichard, 2015) and biological factors such as habitat use and diet (Hussy, 2008). The results of this study also revealed significant variation in otolith shape as a function of physiological and geographical factors. Such variation in otolith shape in \\u003cem\\u003eLiza ramada\\u003c/em\\u003e (Risso, 1827) has been explained by genetic or environmental stress during the development of the species. The effect of sampling location on otolith shape, as demonstrated by the multivariate mixed-effects model, suggests that geography is an important factor in determining otolith morphology. This spatial variation can be attributed to a combination of site-specific environmental factors, such as salinity, water temperature and habitat quality, which can influence fish growth and development.Such results were found by Galley et al., \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2006\\u003c/span\\u003e which states that differences in otolith shape between stocks may be related to environmental conditions and genetic differentiation .Vignon (\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e) found that local environmental conditions cause significant variation in otolith shape. The results confirm that the variation in otolith shapes of \\u003cem\\u003eMugil cephalus\\u003c/em\\u003e is associated with the different geographical regions of the species. This is very similar to the results reported by other studies that have used the same analysis to discriminate stocks and have obtained satisfactory results, in particular the study on the discrimination of fish populations in the Atlantic and Mediterranean seas (Messaoud et al., \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e; Jemaa et al., \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003eb; Neves et al., \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e, Houeto et al., 2023) by analysing otolith shapes.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgments:\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eI would like to express my sincere gratitude to Dr Kakpo C\\u0026eacute;saire, CEO of K-POLYGONE multinational, for the financial support you provided for my research work. Your interest and encouragement were essential elements that enriched this experience.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthical approval\\u003c/strong\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe Laboratory of Ecology, Biology and Physiology of Aquatic Organisms and the Laboratory of Biodiversity, Biotechnology and Climate Change of the Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia, have approved this research. In addition, all procedures in this study were carried out in accordance with the Guidelines for the Appropriate Conduct of Animal Experiments issued by the University of Tunis El Manar, Tunis, Tunisia (No. 1474 certified on August 14, 1995), as well as all applicable international, national and/or institutional guidelines for the care and use of animals in research.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003enot applicable \\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and material\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eOtoliths, otolith images, Excel spreadsheet and python codes used\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eHF, MT ,KM ont r\\u0026eacute;dig\\u0026eacute; le texte principal du manuscritNA, SM statistique et figuresTous les auteurs ont r\\u0026eacute;vis\\u0026eacute; le manuscrit.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n \\u003cli\\u003eAdjibayo Houeto MF, Mejri M, Bakkari W, Bouriga N, Chalh A, Shahin AAAB, Quignard J-P, Trabelsi M, Ben Faleh A (2024). 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Fish stocks of Urophycis brasiliensis revealed by otolith fingerprint and shape in the Southwestern Atlantic Ocean. Estuar. Coast Shelf Sci. 229, 106406.\\u003c/li\\u003e\\n \\u003cli\\u003eBivand, R. S., Pebesma, E., and Gomez-Rubio, V. 2013. Applied spatial data analysis 502 with R, Second edition. Springer, New York. 405 pp.\\u003c/li\\u003e\\n \\u003cli\\u003eBoehlbwt, G.M.I. (1985). Using objective criteria and multiple regression mdels for age deteminbicsn in fishes. Fish. Bull. 83: 103-1 17.\\u003c/li\\u003e\\n \\u003cli\\u003eCardona L. (2000). Effects of salinity on the habitat selection and growth performance of Mediterranean flathead grey mullet \\u003cem\\u003eMugil cephalus\\u003c/em\\u003e (Osteichthyes, Mugilidae). Estuarine Coastal and Shelf Science, 50(5):727-737\\u003c/li\\u003e\\n \\u003cli\\u003eCampana, S.E. (1990). How reliable are growth backcalculations based on otolitks? Can. J. Fish. Aquat. Sci. 47: 2219-2227.\\u003c/li\\u003e\\n \\u003cli\\u003eChang, M.Y.; Geffen, A.J. (2013). Taxonomic and geographic influences on fish otolith microchemistry. Fish Fish, 14: 458\\u0026ndash;492.\\u003c/li\\u003e\\n \\u003cli\\u003e\\u0026nbsp;FAO. (1990). FAO species catalogue. Gadiform Fishes of the world (Order Gadiformes). An Annotated and Illustrated Catalogue of Cods, Hakes, Grenadiers and other Gadiform Fishes Known to Date.Daniel M.Cohen Tadashi Inada Tomio Iwamoto Nadia Scialabba. FAO Fisheries Synopsis, 10(125). Rome, FAO. 1990. 442 p.\\u003c/li\\u003e\\n \\u003cli\\u003eFox, J., Weisberg, S. (2011). 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Ecol. 364: 35\\u0026ndash;41.\\u003c/li\\u003e\\n \\u003cli\\u003eH\\u0026uuml;ssy, K., Mosegaard, H., Albertsen, C.M., Nielsen, E.E., Hemmer-Hansen, J., Eero, M. (2016). Evaluation of otolith shape as a tool for stock discrimination in marine fishes using Baltic Sea cod as a case study. Fish. Res. 174: 210\\u0026ndash;218.\\u003c/li\\u003e\\n \\u003cli\\u003eIbanez, A.L., Hernandez-Fraga, K., Alvarez-Hernandez, S. (2017). Discrimination analysis of phenotypic stocks comparing fish otolith and scale shapes. Fish. Res. 185: 6\\u0026ndash;13.\\u003c/li\\u003e\\n \\u003cli\\u003eJemaa, S.; Bacha, M.; Khalaf, G.; Dessailly, D.; Rabhi, K. and Amara, R. (2015). What can otolith shape analysis tell us about population structure of the European sardine, Sardina pilchardus, from Atlantic and Mediterranean waters?\\u0026nbsp;J. Sea. Res., 96: 11\\u0026ndash;17.\\u003c/li\\u003e\\n \\u003cli\\u003e\\u0026nbsp;Lal\\u0026egrave;y\\u0026egrave;, P., Niyonkuru, C., Moreau, J., Teugels, G.G. (2003).\\u0026nbsp;Spatial and seasonal distribution of the ichthyofauna of Lake Nokou\\u0026eacute;, Benin, West Africa. African Journal of Aquatic Science, 28: 151\\u0026ndash;161.\\u003c/li\\u003e\\n \\u003cli\\u003e\\u0026nbsp;Lederoun D, Lal\\u0026egrave;y\\u0026egrave; KR, Boni AR, et al.\\u0026nbsp;Length\\u0026ndash;weight and length\\u0026ndash;length relationships of some of the most abundant species in the fish catches of Lake Nokou\\u0026eacute; and Porto-Novo Lagoon (Benin, West Africa) . Lakes \\u0026amp; Reserv. 2018;00:1\\u0026ndash;7\\u003c/li\\u003e\\n \\u003cli\\u003eLee C.S. and Menu A. (1981). Effects of salinity on egg development and hatching in Grey mullet, \\u003cem\\u003eM. cephalus\\u003c/em\\u003e, L. Jr Fish Biol, 19(2):179-188.\\u003c/li\\u003e\\n \\u003cli\\u003eLee C.S., Tamaru C.S., Kelley C.D., Moriwake A., Miyamoto G.T. (1992) The effect of salinity on the induction of spawning and fertilization in the striped mullet, Mugil cephalus. Aquaculture, 102: 289-296.\\u003c/li\\u003e\\n \\u003cli\\u003eLombarte, A. et Cruz, A. (2007). Otolith size trends in marine fish communities from different depth strata. J. Fish Biol, 71: 53\\u0026ndash;76.\\u003c/li\\u003e\\n \\u003cli\\u003eMartin, G.B. et Thorrold, S.R. (2005). Temperature and salinity effects on magnesium, manganese, and barium incorporation in otoliths of larval and early juvenile spot Leiostomus xanthurus.\\u0026nbsp;Mar. Ecol. Prog. Ser, 293: 223\\u0026ndash;232.\\u003c/li\\u003e\\n \\u003cli\\u003eMah\\u0026eacute;, K., Gourtay, C., BledDefruit, G., Chantre, C., de Pontual, H., Amara, R., et al.\\u0026nbsp;(2019). Do environmental conditions (temperature and food composition) affect otolith shape during fish early-juvenile phase? An experimental approach applied to European Seabass (Dicentrarchus labrax). J. Exp. Mar. Biol. Ecol. 521: 151239\\u003c/li\\u003e\\n \\u003cli\\u003eMessaoud, H.; Bouriga, N.; Daly Yahia, M.N.; Boumaiza, M.; Faure, E.; Quignard, J.P. and Trabelsi, M. (2011).\\u0026nbsp;Discrimination de trois populations d\\u0026rsquo;anchois du genre Engraulis (Clupeiforme, Engraulidae) des c\\u0026ocirc;tes Tunisiennes par analyse de forme des otolithes. Bulletin de l\\u0026apos;Institut National des Sciences et Technologies de la Mer. 38.\\u003c/li\\u003e\\n \\u003cli\\u003eMille, T., Mah\\u0026eacute;, K., Villanueva, C.M., de Pontual, H., Ernande, B. (2015).\\u0026nbsp;Sagittal otolith morphogenesis asymmetry in marine fishes. J. Fish Biol., 87: 646-663.\\u003c/li\\u003e\\n \\u003cli\\u003eMonteiro, L.R., Di Beneditto, A.P.M., Guillermo, L.H., Rivera, L.A. (2005). Allometric changes and shape differentiation of sagitta otoliths in sciaenid fishes.\\u0026nbsp;Fish. Res, 74: 288\\u0026ndash;299.\\u0026nbsp;\\u003c/li\\u003e\\n \\u003cli\\u003e\\u0026nbsp;Niasse, M., Afouda, A., Amani. A. (2004). R\\u0026eacute;duire la vuln\\u0026eacute;rabilit\\u0026eacute; de l\\u0026apos;Afrique de l\\u0026apos;ouest aux impacts du climat sur les ressources en eau, les zones humides et la d\\u0026eacute;sertification : El\\u0026eacute;ments de strat\\u0026eacute;gie r\\u0026eacute;gionale de pr\\u0026eacute;paration et d\\u0026apos;adaptation. UICN, Gland, Suisse et Cambidge, Royaume-uni.\\u003c/li\\u003e\\n \\u003cli\\u003eMurashige R., Bass P., Wallace L., Molnar A., Eastham B., Sato V., Tamaru C., Lee C. S. (1991).\\u0026nbsp;The effect of salinity on the survival and growth of striped mullet (Mugil cephalus) larvae in the hatchery. Aquaculture, 96(3-4): 249-254.\\u003c/li\\u003e\\n \\u003cli\\u003eNeves, J.; Silva, A.A.; Moreno, A.; Ver\\u0026iacute;ssimo, A.; Santos, A.M. and Garrido, S. (2021). Population structure of the European sardine Sardina pilchardus from Atlantic and Mediterranean waters based on otolith shape analysis. Fish. 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Modern Applied Statistics with S, 4th edn, 761 Springer, New York. 446 pp\\u003c/li\\u003e\\n \\u003cli\\u003eVignon, M. (2012). Ontogenetic trajectories of otolith shape during shift in habitat use: interaction between otolith growth and environment. J. Exp. Mar. Biol. Ecol. 420: 26\\u0026ndash;32\\u003c/li\\u003e\\n \\u003cli\\u003eWalsh W. A., Swanson C., Lee C.S., Banno J.E., Eda H. (1989). Oxygen consumption by eggs and larvae of striped mullet, Mugil cephalus, in relation to development, salinity and temperature. Journal of Fish Biology 35(3): 347\\u0026ndash;358.\\u0026nbsp;\\u003c/li\\u003e\\n \\u003cli\\u003eWalsh W. A., Swanson C., Lee C. S. (1991). Combined effects of temperature and salinity on embryonic development and hatching of striped mullet, \\u003cem\\u003eMugil cephalus\\u003c/em\\u003e. Aquaculture, 97(2-3): 281-289.\\u003c/li\\u003e\\n \\u003cli\\u003eZorica, B.; Snovčić, G. and Čıkeś Keč, V. (2010). Preliminary data on the study of otolith morphology of five pelagic fish species from the Adriatic Sea (Croatia). Acta. Adriat., 5: 89\\u0026ndash;96.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4219582/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4219582/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eThis study explores the ecological diversity of otoliths in \\u003cem\\u003eMugil cephalus\\u003c/em\\u003e by analysing data from 190 individuals collected at different sites, including the Porto Novo lagoon, the Cotonou lagoon and Lake Nokou\\u0026eacute;. The results revealed significant differences in otolith morphology, showing significant associations with the biological characteristics of the fish at each site. Analysis of the asymmetry between the right and left sides reveals distinctions between these two aspects. There is a significant structuring of stock units according to otolith shape, with marked differences between the different geographical sampling areas. The asymmetry percentages illustrate marked differences between the study sites, suggesting variations in the impact of environmental factors on otolith morphology. The higher asymmetry percentages observed in the Porto-Novo lagoon and the Cotonou lagoon indicate a different morphological response compared to Lake Nokou\\u0026eacute;, which could be attributable to distinct environmental conditions and specific selective pressures.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Evaluation of otolith shape as an approach to stock discrimination of Mugil cephalus (Linnaeus, 1758) in the lagoon environments of Benin\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-04-22 02:50:29\",\"doi\":\"10.21203/rs.3.rs-4219582/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"2eb45e23-04b0-4345-a1d4-81b57bf442f1\",\"owner\":[],\"postedDate\":\"April 22nd, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-05-13T16:03:21+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-04-22 02:50:29\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4219582\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4219582\",\"identity\":\"rs-4219582\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}