# Environmental effects on otolith morphology variability of European eel, Anguilla anguilla (Linnaeus, 1758), for subpopulation discrimination in Corsica

Rémi Millot, Anaïs Esposito, Charlotte Gerbaud, Antoine Aiello, Yann

Quilichini, Jean-José Filippi

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Rémi Millot, Anaïs Esposito, Charlotte Gerbaud, Antoine Aiello, Yann Quilichini, et al. Environnemental effects on otolith morphology variability of European eel, Anguilla anguilla (Linnaeus, 1758), for subpopulation discrimination in Corsica. Frontiers in Marine Science, 2026, 12, 10.3389/fmars.2025.1717640. [hal-05519448](https://hal.science/hal-05519448v1)

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EDITED BY
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University of Oviedo, Spain

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University of Cagliari, Italy
Claudio D'Iglio,
University of Messina, Italy

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Rémi Millot

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millot02@hotmail.fr

RECEIVED 02 October 2025
REVISED 12 December 2025
ACCEPTED 15 December 2025
PUBLISHED 19 February 2026

CITATION

Millot R, Esposito A, Gerbaud C, Aiello A, Quilichini Y and Filippi J-J (2026) Environmental effects on otolith morphology variability of European eel, *Anguilla anguilla* (Linnaeus, 1758), for subpopulation discrimination in Corsica. *Front. Mar. Sci.* 12:1717640. doi: 10.3389/fmars.2025.1717640

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© 2026 Millot, Esposito, Gerbaud, Aiello, Quilichini and Filippi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Environmental effects
on otolith morphology
variability of European eel,
*Anguilla anguilla* (Linnaeus,
1758), for subpopulation
discrimination in Corsica

Rémi Millot¹*, Anaïs Esposito²,³, Charlotte Gerbaud¹,³,
Antoine Aiello¹, Yann Quilichini³ and Jean-José Filippi¹

¹Unité d'Appui et de Recherche (UAR) CNRS 3514 STELLA MARE, Université de Corse Pasquale Paoli, Lieu-dit U Casone, lido de la Marana, Biguglia, France, ²Aix-Marseille Université, Université de Toulon, CNRS/INSU, IRD, Mediterranean Institute of Oceanography (MIO), UM 110, Campus universitaire de Luminy, Marseille, France, ³Unité Mixte de Recherche (UMR) CNRS 6134 SPE, Université de Corse Pasquale Paoli, Campus Grimaldi, Corte, France

Otolith shape analysis is an efficient tool for fish stock identification. However, due to insufficient research, it remains still poorly understood concerning the European eel (*Anguilla anguilla*), a highly migratory catadromous and panmictic species. The aim of this study is to discriminate the subpopulations of *A. anguilla* from rivers and two lagoons (three sites) from Corsican continental waters using morphological variations in otolith shape. The otolith shape was described by indices of shapes and by geometric morphometric shape, to understand how otolith morphology changes with eel growth and across contrasting habitats. In this study, the shape of each otolith (N = 305) was described with one landmark and ninety-nine semi-landmarks and by eight shape indices (form factor, aspect ratio, ellipticity, circularity, roundness, rectangularity, squareness and solidity). Results indicate that otolith shape is highly marked for the larger compared to smaller sizes, particularly for the individuals from the lagoons. The slight differences in the small otoliths appear to be due to the acquisition of the shape during the glass eel stage in the marine environment whereas the difference marked in the shape of the large otoliths would be due to the variability of environmental conditions, underlying marked change in otolith shape during growth.

KEYWORDS

Anguilla anguilla, European eel, landmarks, otolith shape, shape indices
# 1 Introduction

The European eel *Anguilla anguilla* (Linné and Salvius, 1758) is a catadromous, semelparous and panmictic species (Als et al., 2011) inhabiting in all types of Northern and Western European and Northern African freshwater and brackish habitats as well as in the Mediterranean Sea. It exhibits a complex life cycle that consists of five stages of metamorphosis: leptocephalus larvae, glass eel, elver, yellow eel and silver eel. Silver eels migrate to the Sargasso Sea to reproduce (Wright et al., 2022). All European eels constitute a single, and randomly mating stock (Dennewitz et al., 2005). Despite their adaptability, and resistance to different environment, the population suffered a drastic decline during the last decades. For example, the recruitment of European eel declined to just 1-10% of the levels recorded from pre-1980s (Magnusson and Dekker, 2021). According to the IUCN, the species is listed as critically endangered (CR) (Pike et al., 2020). This decline is due to the synergistic effect of several factors, such as: barriers to migration, habitat degradation, over-exploitation by fisheries, pollution, climatic change, parasites (particularly *Anguillicola crassus* Kuwahara, Kuwahara et al., 1974), or legal and illegal exploitation and trade (Dekker, 2018; Pike et al., 2020; Zupićić et al., 2022). Consequently, governments and environmental organizations have implemented several countermeasures, including the addition of eels to Appendix II of the Convention on International Trade in Endangered Species (CITES) (Iordăchescu et al., 2022).

The otolith is a biomineralized crystalline-organic complex composed principally of calcium carbonate playing a key role in hearing and vestibular functions in teleosts (Campana, 1999). Otoliths are described as a “flight recorder” archiving all the characteristics of the life cycle of individuals (i.e., age, chemical elements encountered, reproductive periods, etc.) and accumulating the elements distinctive of the fish’s environment (Jones, 1992; Campana and Casselman, 1993). Thus, they provide data for the comprehension of stock structure or population connectivity and dynamics. Among those structures, the saccular otolith (sagitta) exhibits significant morphological variability, which has been demonstrated an effective tool for discriminating among local fish stocks and populations (Campana and Casselman, 1993; Stransky et al., 2005; Hüssy et al., 2016; Mapp et al., 2017). Indeed, both endogenous and exogenous factors influence the overall shape and growth pattern of otoliths (Lombarte et al., 2003). Consequently, these otoliths serve as valuable phenotypic markers for examining environmentally-induced variations, proving to be more effective tools than genetic variation itself in the management of endangered species within fisheries (Capoccioni et al., 2011). However, while it is common to differentiate stocks using otolith morphometrics, the underlying reasons for these differences are often unclear. Variability in the sagitta otolith shape has been shown to be attributable to ontogenetic, genetic and environmental influences such as depth, water temperature, salinity, diet regime, substrate type (e.g. Cardinale et al., 2004; Vignon and Morat, 2010; Vignon, 2012; Mille et al., 2016; Clark et al., 2021). Nonetheless, there is increasing interest in utilizing otolith shape as a natural marker for

fish stocks (Cadrin, 2000; Begg et al., 2005; Campana, 2005), as it offers a practical foundation for stock separation that is beneficial for fisheries management (Begg and Waldman, 1999). Indeed, knowledge on stock, subpopulation and population structure is fundamental to fish stock assessments and to identify appropriate fishery management measures (Pita et al., 2016).

The study of otolith shape variability at the intra- and inter-population levels is particularly relevant for the European eel, as this species has extremely limited genetic structuring due to its panmictic reproduction (Als et al., 2011). Therefore, phenotypic markers that incorporate environmental influences, such as otolith morphology, can provide reliable information on local ecological conditions and habitat-related divergence. Otolith shape is known to be highly plastic and sensitive to environmental gradients, including temperature, salinity, latitude, food availability, growth rate, and population density (Vøllestad, 1992; Bevacqua et al., 2006; Melià et al., 2006). As eels adopt a largely sedentary behavior once settled in continental waters (Laffaille et al., 2005), individuals are exposed to local conditions over the long term, which enhances the potential of otolith shape to reflect the specific environmental history of the site. Although only a few studies have applied otolith morphometry to distinguish Mediterranean eel subpopulations—notably Capoccioni et al. (2011) in rivers and those living in Italian brackish lagoons, Milošević et al. (2021) in rivers and lakes in Croatia and Montenegro, and Podda et al. (2023) in rivers and lagoons in Sardinia—these studies consistently show that spatial differences in otolith shape can occur even in genetically homogeneous stocks. According to Podda et al. (2023), otolith shape analysis made it possible to distinguish subpopulations with a reclassification success rate of approximately 75.7%.

In this context, this study aims at studying the otolith morphology of this species in order to detect potential shape differences inter and intra population in continental Corsican waters (i.e. rivers and lagoon areas). The otolith shape was described by shape indices and the contour by the semi-landmarks methods that incorporate information about curves into the classical landmark-based formalism (Bookstein, 1997).

# 2 Materials and methods

## 2.1 Otolith collection

Sagittal otoliths of *A. anguilla* used in this study were obtained from a reference collection in Corsica (see Esposito et al., 2023). The animal study was approved by the Préfecture of Haute-Corse and Corse-du-Sud (ref. N°2B-2021-06-11-00001 of 11 June 2021 and N° 2A-2021-06-29-00002 of 29 June 2021) by regulatory trained agents. Lagoon samples were bought from professional fishermen. Euthanasia was performed in accordance with French legislation (available at https://www.legifrance.gouv.fr/loda/article_lc/ LEGIARTI000027038776). No experiment was conducted on live animals.

European eels were collected at 13 sampling sites across Corsica (France).
(1) Seasonal sampling was conducted in two coastal lagoons, Urbino and Biguglia, from spring 2021 to winter 2021–2022. Specimens were captured by professional fishermen using fyke nets.

(2) Additional sampling was performed from June to October 2021 by electrofishing, in accordance with French legislation and with logistical support from the angling federation (Fédération de la Corse pour la Pêche et la Protection du Milieu Aquatique) and the French Office for Biodiversity (Office Français de la Biodiversité, OFB). This survey covered ten rivers: Abatesco, Fium-Orbo, Golo, Liamone, Prunelli, Rizzanese, Taravo, Tartagine, Tavignano and Travo. Eels were euthanized in compliance with French legislation. In total, 305 A. anguilla were sampled, 80 in the Biguglia and Urbino lagoons and 145 in the rivers (i.e., 15 Abatesco, 15 Fium'Orbo, 11 Golo, 15 Liamone, 15 Prunelli, 15 Rizzanese, 15 Taravo, 14 Tartagine, 15 Tavignago, 15 Travo) (Figure 1). All individuals from river localities were grouped together as river eel subpopulation, Urbino individuals as Urbino lagoon eel subpopulation and Biguglia individuals as Biguglia lagoon eel subpopulation. The sampling was divided into three distinct subpopulations based on marked abiotic differences. The rivers

range in length from 24.8 km to 89.4 km and are less than 3 meters deep. During the year, the mean water temperature is 14.3 °C (min 12 °C, max 18 °C). The study area is located at a sufficient distance from the mouth of the river, and can be considered a freshwater habitat as its salinity is 0 PSU in all seasons. The Biguglia and Urbino lagoons are the two largest (1450 and 790 ha, respectively) and most exploited lagoons of Corsica. The Biguglia lagoon is a shallow lagoon with an average depth of 1.8 meters, characterized by huge seasonal variations in temperature (min 3 °C, max 28 °C), and by a wide range of salinity conditions (min 4 PSU, max 37 PSU). In contrast, the Urbino lagoon, is a deeper lagoon with an average depth of 5 m (max 9 m), with small variations in salinity (min 35 PSU, max 39 PSU) and a temperature range from 9°C to 27°C.

As mentioned above, all individuals from the rivers were pooled for analysis, as ecological conditions were considered globally comparable, although distinct from those of the lagoons in several key parameters. Otoliths from the three sampling sites were analyzed in two separate size classes in order to avoid ontogenetic effect as mentioned by Capoccioni et al. (2011). Thus, otoliths were

<figure><img src="image_4.png" /></figure>
grouped according to major axis length as follows: small (S; [1.2-2.2] mm) and large (L; [2.6-3.6] mm), and the intermediate range was removed from the analysis, allowing evaluation by extremizing the comparison. A total of 182 specimens belonging to the L and S groups were considered for the Urbino lagoon (Urb), Biguglia lagoon (Big) and the Rivers (R) (i.e., Big-S (N = 13), Big-L (N = 19), R-S (N = 51), R-L (N = 39), Urb-S (N = 15), and Urb-L (N = 45)) and were analyzed for their right sagittal otolith shape.

## 2.2 Otolith shape visualization

Undamaged sagitta otolith pairs were extracted from each eel, cleaned gently with water and in an ultrasound tank in order to removed extraneous tissues, then air-dried before being stored in labelled tubes. Each right otolith was placed on the proximal side (sulcus acusticus) and observed under a Zeiss Discovery V20 stereomicroscope (Zeiss AG, Oberkochen, Germany) under reflected light connected to a Sony XCD-U100CR camera (Sony Professional Solutions, Basingstoke, United Kingdom). The high contrast images were thresholded and binarized for contour extraction by ImageJ software (Schneider et al., 2012).

The outline of each photographed otolith was recorded as pixel coordinates (X-Y coordinates) and subsequently reduced to 100 equally spaced points along the contour, using contour length as a parameter, with the tip of the rostrum designated as the origin (Monteiro et al., 2005; Ponton, 2006; Vignon and Morat, 2010). Thus, the tip of the rostrum is the reference point referred to as a landmark and the remaining 99 points as semi-landmarks (Figure 2A). The landmark and semi-landmark coordinates were digitized utilizing tpsDig2 version 2.10, part of the TPS package developed by Rohlf (2006). To correct any bending energy in the mean reference form, TpsRelw version 1.45 was employed (Green, 1996; Bookstein, 1997), which established the criteria for adjusting semi-landmarks along the outlines (Rohlf and Slice, 1990). Generalized orthogonal least squares Procrustes superimpositions of landmark and semi-landmark coordinates were conducted using Morpho-J software, version 1.02d (Klingenberg, 2011) and were employed for both qualitative and quantitative shape analyses.

## 2.3 Procedure for otolith shape indices calculation

Otolith size indices, such as otolith length (OL; mm), otolith height/width (OH; mm), otolith perimeter (OP; mm), and otolith area (OA; mm²), were measured on ImageJ software (Figure 2B). The otoliths were weighed to nearest 0.0001g with Ohaus Pioneer Analytical Balance (OHAUS, Nänikon, Switzerland) (OW; g). Furthermore, seven indices related to otolith shape were calculated using the following formulas (Tuset et al., 2003; Moore et al., 2022):

i. form factor (FF) [FF = (4πOA)/(OP²)];

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /><figcaption>FIGURE 2
(A) Digitized lateral view of an otolith of A. Anguilla showing the semi-landmarks and landmarks. Point 2 to 100 (red points) are semi-landmarks equally spaced along the contour and point 1 (blue point) is the landmark located in the tip of the rostrum; (B) A anguilla otolith, lateral view. OH, otolith height/width; OL, otolith length.</figcaption></figure>

ii. aspect ratio (AR) [AR = OL/OH];

iii. ellipticity (E) [E = (OL - OH)/(OL + OH)];

iv. circularity (C) [C = OP²/OA];

v. roundness (RO) [RO = (4OA)/(πOL²)];

vi. rectangularity (RE) [RE = OA/(OL x OH)];

vii. squareness (SQ) [SQ = OA/(OL x OW)].

Nevertheless, in order to avoid the possible size effect on otolith morphometric indices, a correction has been applied. Indeed, without correction on allometry, it would be difficult to determine with certainty whether the observed differences are truly indicative of interspecific variations or merely a consequence of collecting fish of different sizes. Consequently, it was essential to account for allometric effects to guarantee precise interpretation of otolith data. Thus, the following correction equation has been applied to standardize all variables and eliminate the allometric impact of fish length on the size and shape of otoliths (Elliott et al., 1995; Lleonart et al., 2000; Zischke et al., 2016).

$$M_S = M_o \left(\frac{\bar{x}}{x}\right)^b$$
Where,
Ms = standardized (size-adjusted) measurement;
Mo = original parameter (size and shape indices);
\bar{x} = average size parameter (TL) for all datasets;
x = size parameter (TL) of each fish species;
b = slope of the regression between log Mo and log X.

## 2.4 Statistical analysis

### 2.4.1 Shape indices analysis

The Shapiro-Wilk's and Levene's tests were applied on residual values to verify the normality and homogeneity, respectively. To compare shape indices, a univariate analysis of variance (ANOVA) was applied. When significant differences were detected, Tukey's honestly significant difference (HSD) test was performed, provided that the assumptions for its application were met. If not, a non-parametric Kruskal-Wallis test was applied, followed by Dunn's test for *post-hoc* comparisons. Furthermore, principal component analysis (PCA) was performed to identify the shape indices that contributed most significantly to distinguishing between groups, e.g., sites for small otoliths; sites for large otoliths or sites for both small and large otoliths. All statistical analyses were performed using R software v.4.2.0 (R Core Team, 2022) and all data are presented as the mean ± standard deviation (SD). The following packages were used: rstatix (0.7.2), ggpubr (0.6.0.999), ggplot2 (3.4.2), stats (3.6.2), FactoMineR (2.8), factoextra (1.0.7), psych (2.3.3), GGally (2.1.2).

### 2.4.2 Multivariate morphometric analysis

The Principal Component Analysis (PCA), Canonical Variate Analysis (CVA), and Discriminant Function Analysis (DFA) were used to evaluate the variation of shape and detect differences between the sites and otolith size. The PCA was performed using a covariance matrix from the multivariate regression residues (Jolliffe, 2002) in order to explore the main variation patterns in the data and trends among groups of interest. The CVA shows a general view of the shape variations and the DFA was used to generate the final variations of shape. For the CVA and DFA, the significant differences were tested using a permutation test (n = 10,000) for the Procrustes distance. The Procrustes distance was preferred to Mahalanobis distance because the first is a measurement of the absolute amount and the second is a measurement of shape variation (Klingenberg and Monteiro, 2005). Ultimately, a cluster analysis from the residual data from the multivariate regression was used for better visualization of group formation for each sampling site and size classes (i.e., group: Big-S, Big-L, Urb-S, Urb-L, R-S and R-L). These results were visualized in dendrogram format. Then, the shape variations obtained from PCA, DFA, and CVA analysis were represented by means of deformation grids and wireframe graphics. All statistical analysis were performed with Morpho-J software, version 1.02d (Klingenberg, 2011) and cluster analysis on R software (R Core Team, 2022) with package: stats (3.6.2).

# 3 Results

## 3.1 Shape indices analysis

Small otoliths of *A. anguilla* showed limited spatial variation, with no significant differences among sites for most shape indices ($P > 0.05$), except for Roundness, Rectangularity and Squareness ($P < 0.05$). The main contrast involved river eels and those from the Urbino lagoon, as river otoliths were more rounded and less rectangular. Differences between the two lagoons were present but remained moderate (Table 1; Figure 3A). In large otoliths, spatial structuring was much more pronounced. Nearly all shape indices differed significantly among sites ($P < 0.001$), except Rectangularity ($P > 0.05$) (Table 1; Figure 3B). River otoliths were more circular and rounded, with a lower Aspect Ratio, while lagoon otoliths particularly those from Biguglia had higher Aspect Ratio, Ellipticity and Squareness, and lower Roundness. Differences between the two lagoons were also evident but less marked than between rivers and lagoons. Overall, morphological differentiation increased substantially with otolith size, indicating that spatial contrasts become clearer as individuals grow and likely reflect stronger environmental imprinting at later life stages.

Several principal component analyses (PCA) were performed on (1) small, (2) large, and (3) all otoliths. In all cases, the first two components explained more than 70% of the total variation ((1) PCA1 = 37.3%, PCA2 = 32.8%; (2) PCA1 = 46.6%, PCA2 = 26.6%; (3) PCA1 = 43.2%, PCA2 = 28.9%) (Figures 4A–C). However, for small otoliths, the strong overlap of the 95% confidence ellipses indicated no morphological separation among sites, whereas large otoliths showed clear and distinct site-specific clusters. The general PCA confirmed this pattern. Overall, the analyses reveal a sharp contrast: small otoliths display overlapping morphologies, while large otoliths show pronounced morphological differences between sites.

## 3.2 Multivariate morphometric analysis

The DFA indicated significant differences in the otoliths shape between all groups ($P < 0.05$), except between Big-S vs R-S, Big-S vs R-L and Big-S vs Urb-S ($P > 0.05$) (Table 2). Overall, large otoliths exhibited greater inter-site variation than small otoliths, indicating that morphological differentiation increases with growth (Table 2).

Thus, for (1) small otoliths, differences were limited to Urb-S and R-S, with Urb-S otoliths narrower and featuring a more pronounced post-rostrum, giving a slightly rectangular shape, while Big-S otoliths overlapped with both groups, reflecting limited spatial differentiation at small size (Figure 5A). In contrast, (2) large otoliths showed clear and significant inter-site differences. Lagoon otoliths (Urb-L and Big-L) had more developed rostrum and post-rostrum, resulting in elongated shapes, whereas river otoliths (R-L) remained broader and more circular. Urb-L otoliths also had a more pronounced excisura than Big-L. These
<table><caption>TABLE 1 Variations of otolith shape indices across the three sites by otolith group.</caption><thead><tr><th rowspan="3">Variables</th><th colspan="6">Small Otolith (S)</th><th colspan="6">Large Otolith (L)</th><th rowspan="3">Test</th></tr><tr><th colspan="2">Rivers (n = 51)</th><th colspan="2">Biguglia (n = 13)</th><th colspan="2">Urbino (n = 15)</th><th rowspan="2">Sign.</th><th rowspan="2">Test</th><th colspan="2">Rivers (n = 39)</th><th colspan="2">Biguglia (n = 19)</th><th colspan="2">Urbino (n = 45)</th><th rowspan="2">Sign.</th></tr><tr><th>Mean ± SD</th><th>Min-Max</th><th>Mean ± SD</th><th>Min-Max</th><th>Mean ± SD</th><th>Min-Max</th><th>Mean ± SD</th><th>Min-Max</th><th>Mean ± SD</th><th>Min-Max</th><th>Mean ± SD</th><th>Min-Max</th><th>Mean ± SD</th><th>Min-Max</th></tr></thead><tbody><tr><td>Circularity</td><td>0.78 ± 0.03</td><td>0.73-0.83</td><td>0.78 ± 0.02</td><td>0.73-0.81</td><td>0.78 ± 0.02</td><td>0.75-0.81</td><td>P&gt;0.05</td><td>Anova</td><td>0.77 ± 0.03</td><td>0.70-0.82</td><td>0.74 ± 0.03</td><td>0.68-0.78</td><td>0.74 ± 0.04</td><td>0.66-0.80</td><td><b>P&lt;0.001</b></td><td>Anova</td></tr><tr><td>AR</td><td>1.40 ± 0.07</td><td>1.26-1.58</td><td>1.45 ± 0.10</td><td>1.33-1.64</td><td>1.45 ± 0.05</td><td>1.38-1.57</td><td>P&gt;0.05</td><td>Anova</td><td>1.47 ± 0.1</td><td>1.31-1.89</td><td>1.61 ± 0.08</td><td>1.48-1.75</td><td>1.53 ± 0.09</td><td>1.37-1.73</td><td><b>P&lt;0.001</b></td><td>KS</td></tr><tr><td>FormFactor</td><td>0.78 ± 0.03</td><td>0.72-0.86</td><td>0.78 ± 0.02</td><td>0.73-0.81</td><td>0.78 ± 0.02</td><td>0.75-0.81</td><td>P&gt;0.05</td><td>Anova</td><td>0.77 ± 0.03</td><td>0.70-0.82</td><td>0.74 ± 0.03</td><td>0.68-0.78</td><td>0.74 ± 0.04</td><td>0.66-0.80</td><td><b>P&lt;0.001</b></td><td>Anova</td></tr><tr><td>Roundness</td><td>0.72 ± 0.04</td><td>0.63-0.80</td><td>0.69 ± 0.05</td><td>0.61-0.75</td><td>0.69 ± 0.03</td><td>0.64-0.73</td><td><b>P&lt;0.05</b></td><td>Anova</td><td>0.68 ± 0.04</td><td>0.53-0.76</td><td>0.62 ± 0.03</td><td>0.57-0.68</td><td>0.65 ± 0.04</td><td>0.58-0.73</td><td><b>P&lt;0.001</b></td><td>Anova</td></tr><tr><td>Ellipticity</td><td>0.17 ± 0.03</td><td>0.11-0.23</td><td>0.17 ± 0.03</td><td>0.13-0.21</td><td>0.17 ± 0.03</td><td>0.13-0.21</td><td>P&gt;0.05</td><td>Anova</td><td>0.20 ± 0.03</td><td>0.15-0.32</td><td>0.24 ± 0.04</td><td>0.15-0.29</td><td>0.20 ± 0.03</td><td>0.14-0.27</td><td><b>P&lt;0.001</b></td><td>Anova</td></tr><tr><td>Rectangularity</td><td>0.76 ± 0.03</td><td>0.71-0.89</td><td>0.75 ± 0.04</td><td>0.70-0.81</td><td>0.80 ± 0.03</td><td>0.76-0.86</td><td><b>P&lt;0.001</b></td><td>KS</td><td>0.78 ± 0.05</td><td>0.54-0.83</td><td>0.77 ± 0.03</td><td>0.70-0.82</td><td>0.78 ± 0.03</td><td>0.71-0.84</td><td>P&gt;0.05</td><td>KS</td></tr><tr><td>Solidity</td><td>0.97 ± 0.01</td><td>0.94-0.99</td><td>0.97 ± 0.01</td><td>0.96-0.98</td><td>0.97 ± 0.01</td><td>0.96-0.98</td><td>P&gt;0.05</td><td>KS</td><td>0.97 ± 0.01</td><td>0.96-0.99</td><td>0.96 ± 0.01</td><td>0.95-0.98</td><td>0.97 ± 0.01</td><td>0.94-0.98</td><td><b>P&lt;0.001</b></td><td>Anova</td></tr><tr><td>Squareness</td><td>0.49 ± 0.12</td><td>0.18-0.82</td><td>0.54 ± 0.09</td><td>0.41-0.70</td><td>0.43 ± 0.12</td><td>0.24-0.73</td><td><b>P&lt;0.05</b></td><td>KS</td><td>0.32 ± 0.06</td><td>0.18-0.47</td><td>0.30 ± 0.05</td><td>0.20-0.41</td><td>0.39 ± 0.06</td><td>0.28-0.50</td><td><b>P&lt;0.001</b></td><td>Anova</td></tr></tbody></table>

Significant differences between sites are in bold. The data includes sample size (n), the arithmetic mean ± SD, and the minimum - maximum values. OH, otolith height/width; OL, otolith length; C, circularity; AR, aspect-ratio.

patterns suggest that growth amplifies site-specific morphological differences, with lagoon otoliths exhibiting the strongest deformities, while river otoliths retain a predominantly circular shape (Figures 6, 5B, C).

Cluster analysis dendrogram based on Procrustes distances supported these results, identifying two main clusters: one comprising Big-L and Urb-L, and another containing the remaining groups. Within the latter, Urb-S formed a distinct sub-cluster, while R-S clustered with R-L and Big-S, highlighting a clear separation between large and small otoliths in lagoons, in contrast to rivers (Figure 5D). Canonical variate analysis (CVA) further distinguished the groups, with the first three axes explaining 81.83% of the variation (CV1 = 39.21%, CV2 = 29.29%, CV3 = 13.33%) (Figure 5E). CV1 reflected variations in the rostrum, anti-rostrum, and excisura, CV2 captured differences in otolith width, and CV3 variations at the post-rostrum. These results indicate that otolith shape is strongly influenced by both size and site, with large lagoon otoliths showing the most distinctive morphologies, likely reflecting growth-related changes and local environmental conditions.

## 4 Discussion

In this study, the term subpopulation was deliberately used instead of stock. Although some previous authors have referred to eel stocks, this term is generally associated either with genetically distinct units or with fisheries management units, none of which are deeply assessed in this study. Since the European eel is a panmictic species and this study does not evaluate genetic structure nor fishing-based management divisions, subpopulation is more appropriate to describe groups of individuals inhabiting different ecological habitats within Corsica.

As already emphasized, the intraspecific quantitative significance of allometric shape changes in otoliths were poorly documented (Hüssy, 2008; Capoccioni et al., 2011; Vignon, 2012). The present study aimed to investigate the otolith morphological differences for subpopulations of *A. anguilla* from Corsican continental waters (i.e., rivers and two lagoons), according to two size classes. Two complementary approaches were used: (1) shape indices analysis and (2) multivariate morphometric analysis, to assess how otolith morphology varies with growth and habitat ecology in this panmictic and sedentary species (Als et al., 2011; Laffaille et al., 2005). The results of different analysis showed that otolith shape differed among the three subpopulations suggesting that otolith shape could be a valuable tool for discriminating eel subpopulations inhabiting distinct habitats. These findings are consistent with previous studies in Mediterranean eel populations, which reported habitat-specific differences in otolith morphology reflecting environmental influences on growth and development (Capoccioni et al., 2011; Milošević et al., 2021; Podda et al., 2023). As noted by Capoccioni et al. (2011), otolith shape in European eels changes during ontogeny and is modulated differently depending on habitat conditions. Furthermore, larger otoliths provide better discriminatory power than smaller ones, likely because their greater
<figure><img src="image_7.png" /><figcaption>FIGURE 3
Boxplot of shape indices as a function of sites for (A) small otolith and (B) large otolith with statistical significance: ****(P < 0.0001), ***(P < 0.001), **(P < 0.01) and *(P < 0.05).</figcaption></figure>

growth allows morphological differences to accumulate and become more pronounced within a given habitat.

This study show that there are fewer differences in the shape of small otoliths than in large otoliths. This low variability in the shape of otoliths from rivers suggests, as reported by Capoccioni et al. (2011), differential habitat conditioning necessarily leading to otolith shapes during the later stages of growth, due to a delayed environmental response. Thus, small otoliths probably retain a similar shape to those of the post-metamorphic stage, influenced by the marine conditions in which leptocephali and elvers develop (Lecomte-Finiger, 1992). After migrating to continental waters, growing eels modify the shape of their otoliths according to local ecological conditions, such as salinity and temperature, which are factors influencing other fish species (Mosegaard et al., 1988; Cardinale et al., 2004).

Furthermore, in this study, the otoliths of individuals from lagoons have a similar shape (elongated and irregular) whereas individuals from rivers retain a circular and regular shape such as reported by Capoccioni et al., 2011; Milošević et al., 2021 and Podda et al., 2023. These differences can be explained by seasonal and daily

variations in salinity (Fabbrocini et al., 2008; Capoccioni et al., 2011) e.g., River individuals are exposed to more homeostatic environmental conditions than lagoon individuals. Indeed, these environments generally tend to be less susceptible to variations in salinity or temperature and depth than brackish estuaries or lagoons (Podda et al., 2021). Several studies have highlighted salinity as one of the main factors characterizing *A. anguilla*'s ecological niche and therefore conditioning its growth rate (Sadler, 1979; Cairns et al., 2009; Lamson et al., 2009). According to Umezawa and Tsukamoto (1991), this factor is involved in the formation of incremental layer deposition (i.e., otolith growth), affecting the shape and size of otoliths due to the different growth rates of each otolith zone (Gauldie, 1993). The frequency and width of depositional layers are controlled by internal factors while also being influenced by variables like temperature changes and feeding (Campana and Neilson, 1985; Morales-Nin, 2000), thus corroborating the observation of Panfili et al. (1990) who classified eels otoliths into two types of sagittae, according to the width of the growth rings, called ‘brackish water type’ and ‘fresh water type’ otoliths respectively. Salinity is therefore a possible explanation for the
<figure><img src="image_8.png" /></figure>

FIGURE 4

Principal component analysis (PCA) plot for otolith shape indices of the three sites analyzed (Biguglia, Urbino and rivers); (A) small otoliths, (B) large otoliths and (C) all otoliths.

difference in shape between individuals from lagoons and rivers. Otoliths from the lagoon specimens are subtle differences, which could possibly be the result of ranges of variation in salinity. Indeed, the Biguglia lagoon is characterized by a wide variation in salinity conditions (min 4 PSU, max 37 PSU) induced by the shallow depth,

unlike the Urbino lagoon which has a small range of variation (min 35 PSU, max 39 PSU). However, the mechanisms through which abiotic environmental variables interact to influence or constrain species growth remain poorly understood (Daverat et al., 2012). Indeed, numerous exogenous factors have been shown to affect
<table><caption>TABLE 2 Statistical results of the pairwise comparisons between the six groups (i.e. for the three sites and two size groups).</caption><thead><tr><th>p-value/Pcr</th><th>R-S</th><th>R-L</th><th>Big-S</th><th>Big-L</th><th>Urb-S</th><th>Urb-L</th></tr></thead><tbody><tr><td>R-S</td><td>-</td><td>0.0222</td><td>0.0236</td><td>0.0531</td><td>0.0300</td><td>0.0399</td></tr><tr><td>R-L</td><td><strong>0.0020</strong></td><td>-</td><td>0.0188</td><td>0.0351</td><td>0.0281</td><td>0.0277</td></tr><tr><td>Big-S</td><td>0.0529</td><td>0.3301</td><td>-</td><td>-</td><td>0.0225</td><td>0.0316</td></tr><tr><td>Big-L</td><td><strong>&lt;0.0001</strong></td><td><strong>0.0002</strong></td><td><strong>0.0013</strong></td><td>-</td><td>0.0449</td><td>0.0243</td></tr><tr><td>Urb-S</td><td><strong>0.0014</strong></td><td><strong>0.0090</strong></td><td>0.2092</td><td><strong>&lt;0.0001</strong></td><td>-</td><td>0.0310</td></tr><tr><td>Urb-L</td><td><strong>&lt;0.0001</strong></td><td><strong>0.0001</strong></td><td><strong>0.0094</strong></td><td><strong>0.0297</strong></td><td><strong>0.0052</strong></td><td>-</td></tr></tbody></table>

Results are reported as Procrustes distances after 10,000 permutation rounds. Pcr, Procrustes distances. Values in bold indicate statistical significance (P < 0.05).

otolith growth. Several studies have identified key determinants such as food availability, depth, water temperature, substrate type, as well as otolith age and size (Lombarte and Lleonart, 1993; Oozeki and Watanabe, 2000; Cardinale et al., 2004; Gagliano and McCormick, 2004; Schulz-Mirbach et al., 2008; Vignon, 2018; Di Franco et al., 2019; Hong et al., 2021).

The results show that the shape indices method does not effectively discriminate between eel subpopulations for small otoliths with very low shape variation. In fact, the PCA does not distinguish between subpopulations, unlike the multivariate method, as DFA showed differences in shape between the lagoons and between the Urbino lagoon and the rivers, but showed no difference between the Biguglia lagoon and the rivers. The multivariate method has the advantage of better describing variations in shape, particularly those resulting from small-scale

effects such as those generated by environmental effects (Mérigot et al., 2007). Nevertheless, the univariate method has proved to be reliable for large otoliths because, as explained above, large otoliths are better at discriminating subpopulations thanks to greater shape variations. Thus, this method can be reliable under certain conditions because it has the advantage of being easier to compare and more intuitive to interpret (Ponton, 2006), unlike the multivariate method (Tuset et al., 2006).

The approaches employed in this study successfully distinguished eel subpopulations occupying different freshwater habitats in Corsica, confirming the relevance of otolith morphology for assessing population structure, as also reported in other European regions (Capoccioni et al., 2011; Milošević et al., 2021; Moura et al., 2022; Podda et al., 2023). The observed morphological variability likely reflects the combined influence of

<figure><img src="image_9.png" /></figure>
<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /><figcaption>FIGURE 6</figcaption></figure>

Shape variation between the small and large otoliths for samples taken in the rivers (A), Biguglia lagoon (B) and Urbino lagoon (C). On the left side, the two configurations overlap, showing the areas variation indicated with grey vector and the right side shows the deforming grids.

endogenous drivers, such as genetics and phylogeny (Zarei et al., 2022), functional adaptations of the inner ear (Parmentier et al., 2001), and acoustic communication (Lombarte and Cruz, 2007) and exogenous factors, with food availability exerting a particularly strong effect (Mille et al., 2016; Assis et al., 2020; D'Iglio et al., 2025). These interacting mechanisms complicate the identification of the specific contribution of environmental variables to otolith shape and size. Limitations related to sample size and the absence of

detailed environmental data further warrant cautious interpretation. Future work incorporating individual traits (sex, size, age) and finer environmental information will be essential to better understand how habitat conditions and environmental variability influence eel growth and otolith characteristics. To this end, this study provides key insights that support European eel management and conservation in Corsica's ecologically important and vulnerable habitats.
## Data availability statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.

## Ethics statement

The animal study was approved by N°2B-2021-06-11-00001 N° 2A-2021-06-29-00002. The study was conducted in accordance with the local legislation and institutional requirements.

## Author contributions

RM: Data curation, Formal Analysis, Investigation, Writing – original draft, Writing – review & editing. AE: Data curation, Investigation, Visualization, Writing – review & editing. CG: Data curation, Investigation, Visualization, Writing – original draft. AA: Supervision, Writing – review & editing. YQ: Funding acquisition, Supervision, Writing – review & editing. J-JF: Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing.

## Funding

The author(s) declared that financial support was received for this work and/or its publication. This research is part of the GERHYCO interdisciplinary project dedicated to water management, ecology, and hydro-ecosystem services in an insular context, and it was financially supported by the Cullettività di Corsica.

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## Acknowledgments

We would like to thank Dr. EDH. Durieux for coordinating the extraction of the otoliths.

## Conflict of interest

The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

## Generative AI statement

The author(s) declared that generative AI was used in the creation of this manuscript.

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