Exploring Life History Traits and Catch Composition of Red Mullet (Mullus barbatus, L. 1758) in the Commercial Trawl Fisheries of the Eastern Aegean Sea

Abstract

The red mullet (Mullus barbatus, Linnaeus 1758) is a commercially vital demersal species in the Eastern Aegean Sea, yet it is subjected to high fishing pressure. This study assesses the population dynamics, growth, and exploitation status of M. barbatus based on 64 commercial trawl surveys conducted between 2022 and 2024 in the Lesvos–Ayvalik region. Length-frequency data identified eight age classes, with dominant cohorts at ages 3 (26.4%) and 5 (25%). The von Bertalanffy growth model estimated an asymptotic length (L∞) of 27.9 cm and growth coefficient (k = 0.21 year⁻¹), indicating a slow growth rate. The estimated fishing mortality (F = 0.74) exceeded natural mortality (M = 0.44), producing an exploitation rate (E = 0.63) that indicates overfishing. The length at 50% capture (LC₅₀ = 10.92 cm) was substantially below the optimal biomass length (Le = 16.6 cm), highlighting gear selectivity issues. Net benefit analysis revealed optimal fishing at 50–85 m depth and during December. These findings underscore the urgent need for improved management, including gear modifications, seasonal closures, and reduced effort, to restore sustainability and protect juvenile fish in the Eastern Aegean trawl fishery.

1. Introduction

The red mullet (Mullus barbatus Linnaeus, 1758) is a widely distributed benthic species, occurring from Western Norway and the English Channel (rarely in the North Sea) southward to Dakar, Senegal, and the Canary Islands, and throughout the Mediterranean and Black Sea [1]. The species inhabits depths of 5–300 m, primarily over gravel, sandy, and muddy substrates on the continental shelf, where it is exploited by both bottom trawl and small-scale fisheries [1,2,3,4,5]. As one of the most important demersal resources in the Mediterranean, M. barbatus has supported substantial fisheries for at least half a century [6,7], with annual Mediterranean landings reported at 13,416 t in 2007–2008 and 2035 t from Turkish coasts alone [8]. Its high economic value has driven numerous studies on its population dynamics and stock status across the region [9,10,11], and annual Turkish catches have fluctuated between 1304.0 t and 3476.4 t over the last decade [12] (Figure 1).

Although M. barbatus is broadly distributed, its abundance and size composition vary markedly with depth. Relative abundance declines with increasing depth [13], and ontogenetic habitat shifts have been documented: individuals under 14 cm total length are largely confined to depths <100 m, whereas larger fish (19–21 cm TL) predominate between 100 and 200 m [14].

Over the past three decades, research has focused on key biological and population dynamics aspects, including age, growth, maturation, mortality, and stock assessments, utilizing methods such as otolith analysis, experimental surveys, and port-based sampling. Studies in Turkish waters [15,16], the Aegean Sea [17,18], and other regions [10,19,20,21] have contributed to a detailed understanding of the species. Comparable research in the Ionian, Levantine, and Adriatic Seas, as well as the Sicilian Strait, has employed von Bertalanffy growth models, length–weight relationships, and gear selectivity analyses to inform sustainable fisheries management.

Knowledge of growth, mortality, and biomass is critical for effective resource estimation and management [22]. Investigations across the Mediterranean, from the Algerian coast [11] to the north coast of Sicily [19], have provided valuable data on population structure and dynamics. These studies, often based on otolith aging and trawl selectivity parameters, have established a foundation for regional stock assessments and conservation strategies, ensuring the species’ sustainability amid growing fishing pressures.

Scales and otoliths are the primary structures used to estimate the age of red mullet, but otolith analysis is generally preferred due to its higher accuracy [23,24]. Scale readings often underestimate older ages, whereas otoliths, despite their own challenges, provide clearer annual increments [24,25,26,27]. Readers must contend with false growth checks, the deposition of reproductive increments, and annuli crowding in older specimens, all of which complicate the identification of the first true annulus [24,28]. Direct validation methods such as mark–recapture, captive rearing, or radiochemical ageing are seldom feasible for this species because of high post-capture mortality (stress, scale loss, and wounds; Ref. [29] and a typical lifespan of only 5–8 years [4,19]. Consequently, uncertainty in annulus interpretation can shift age estimates by a whole year, significantly affecting growth parameter estimates and downstream stock assessment models.

On the other hand, length-at-age data constitute a fundamental input for analytical assessments of exploited fish populations [30,31], especially in multi-species, data-poor contexts like the Mediterranean demersal fishery [32]. Length-at-age models incorporating length-frequency analysis have been carried out for M. barbatus as key tools in Mediterranean stock assessments [4]. Arslan & İşmen [17] applied ELEFAN and otolith readings to data from Saros Bay, finding a significantly higher growth coefficient with ELEFAN compared to otolith-based estimates. Carbonara et al. [23] analyzed Southern Adriatic trawl survey data using Bhattacharya modal decomposition and ELEFAN, producing sex-specific von Bertalanffy parameters. Bianchini & Ragonese [33] synthesized 56 Mediterranean datasets, including direct and indirect growth estimates, to establish a standardized reference growth curve for M. barbatus. Together, these studies highlight the robustness and variability of length-at-age approaches using length-frequency methods and underscore their importance for complementary stock evaluation models.

Lately, studies are starting to explore the life history traits and population dynamics of M. barbatus using data derived from commercial fisheries, particularly in the Mediterranean and Black Sea regions. For instance, Cerim et al. [34] analyzed discard rates and fishing mortality from monthly hauls aboard a commercial trawler operating in the southern Aegean Sea, demonstrating the intense fishing pressure faced by this species. Similarly, Yilmaz et al. [35] applied age-based stock assessment models using data collected during commercial trawling operations in the Black Sea. Yıldız and Karakulak [36] utilized data from commercial landings to estimate growth parameters, age composition, and mortality rates of M. barbatus, highlighting comparable fishing pressures in the region. These studies confirm that commercial fisheries data can yield valuable insights into red mullet population dynamics, complementing and reinforcing findings from experimental research programs. Despite the wealth of knowledge generated from experimental surveys, scientific trawls, and biological sampling, there remains a notable gap in data derived directly from commercial fisheries, particularly on parameters such as the biological reference points, discards versus retained fractions of the species, and fishery-dependent age and length composition. While M. barbatus is a heavily exploited species by trawl fleets, relatively few studies incorporate high-resolution data from commercial vessels to assess stock status and exploitation patterns. Addressing this gap is crucial for aligning biological knowledge with real-world fishing practices and for informing practical, sustainable management strategies. Moreover, despite the wealth of biological studies on M. barbatus, there remains a limited understanding of how fishing efficiency and discards vary across depth strata and seasons within commercial trawl operations. Identifying the most profitable depth ranges and periods for red mullet capture, while minimizing discards, is essential for improving fishery performance and supporting sustainable management. This study aims to address this gap by integrating biological assessments with spatiotemporal analyses of landings and discards.

2. Materials and Methods

2.1. Study Area and Sampling Methodology

This research was carried out over four commercial trawling seasons in the Eastern Aegean Sea, specifically in the area between Lesvos (or Lesbos) Island and Ayvalik (Figure 2).

The study area hosts a total of 23 active bottom trawling vessels, as documented by local fisheries cooperatives. Artisanal fisheries employing gillnets and trammel nets operate primarily in nearshore waters, maintaining spatial separation from trawling grounds. This distinct zonation arises from two principal factors: (1) the substantial risk of gear damage, wherein mobile trawl nets may destroy stationary artisanal gear, and (2) economic considerations, as small-scale fishers would incur prohibitive fuel costs by operating farther offshore [37,38]. Under Turkish fisheries regulations, bottom trawling is permitted seasonally from 1 September to 15 April, with no area-specific management measures implemented beyond the standard national commercial fishing regulations [39]. This regulatory framework lacks spatial or temporal adaptations to address local fishing dynamics or potential gear conflicts in the study area.

Between September 2022 and October 2024, 64 trawl surveys were conducted at depths of 25 to 85 m. All trawl operations were conducted on the commercial trawler Dülger Balıkçılık (25.7 m long, equipped with a 940 hp main engine). Each tow averaged 3 h at a speed of about 2.8 knots. The trawling gear was a modified design made entirely of knotless polyethylene (PE), featuring a 900-mesh circumference in the fishing circle. The codend had a 44 mm mesh size and was fitted with an 88 mm mesh protective bag to reduce catch damage. Specimens of M. barbatus were identified on board the commercial trawler using morphological characteristics described in the FAO species identification guide for fishery purposes [40]. During each survey, the total length of individuals from all commercial species captured was measured for both the retained and discarded portions, along with the total weight of the retained and discarded fractions. Turkish fisheries regulations establish a 12 cm minimum landing size for red mullet [41], which applies uniformly across all commercial fishing sectors.

2.2. Statistical Analysis

Exploratory data analysis (EDA) was conducted to characterize the length distribution of red mullet following established methods [42]. Lengths of retained and discarded catch fractions were compared using a two-sample t-test with a significance level of 0.05. Prior to the t-test, data normality was assessed using the Shapiro–Wilk test, and equality of variances was evaluated with a variance ratio test to ensure test assumptions were met [43]. Statistical analysis was performed with Jamovi software (Version 2.3.28; Sydney, Australia).

The net benefit (landings minus discards) of fishing for M. barbatus across four depth ranges (25–35 m, 35–40 m, 40–50 m, and 50–85 m) and across five months (September, October, November, December, January) was employed to determine the optimal depth for fishing operations and fishing month, respectively. A one-way ANOVA was performed to test significant differences in net benefit across depths and months, followed by a Tukey HSD post hoc test if the ANOVA was significant (p < 0.05) [44]. Additionally, pairwise t-tests were performed using the ggpubr package [45] in R (Version 4.5.1) to compare net benefit between depth ranges and months. Results were visualized using ggplot2 [46], displaying net benefit distributions by depth and annotated with significance indicators from the pairwise comparisons.

Spatial analyses were conducted in R (Version 4.5.1; R Core Team, 2023) using established packages for geostatistical visualization [47,48]. Bathymetric data were sourced from NOAA’s ETOPO1 global model [49], with coastline vectors from Natural Earth [50]. Catch Per Unit of Effort (CPUE) interpolation followed Akima’s spline method [51], and contour labeling was implemented with the metR package [52]. The interpolated data were converted into a data frame for visualization using the ggplot2 package [46]. A high-resolution heatmap was generated to visualize spatial gradients in CPUE, following established methods for fishery data [53].

2.3. Age Composition and Growth

Length-frequency distributions (LFDs) were pooled into 0.5 cm size classes and partitioned into age groups using Bhattacharya’s method [54] to identify cohort-specific mean lengths. Cohort separation was validated using the separation index, implemented in FiSAT II (Version 1.2.2; FAO; Rome, Italy). Growth of M. barbatus was modeled using the Electronic LEngth Frequency ANalysis (ELEFAN) system [55]. Monthly LFDs were fitted to a seasonally oscillating von Bertalanffy growth function (VBGF), with modes of length-frequency distributions (LFQs) tracked over time to estimate growth progression [56]. Response Surface Analysis (RSA) was applied to VBGF-fitting, systematically evaluating combinations of growth parameters (K, L∞) to identify the best-fit model. The response surface peak provided the optimal estimates of growth rate and asymptotic length.

Growth parameters were calculated using the von Bertalanffy growth equation [57] (Equation (1)), which models fish length as a function of age.

$$\mathrm{L}\mathrm{t}=\mathrm{L}\mathrm{\infty }\times \left(1-{\mathrm{e}}^{-k\times \left(\mathrm{t}-t_0\right)}\right)$$

(1)

where L∞ is the asymptotic length, k is the growth rate, and t₀ is the theoretical age at zero length.

The growth performance index (φ′) (in length) was estimated using the von Bertalanffy parameters [58] (Equation (2)).

$${\phi }^{\prime }=\mathrm{l}\mathrm{o}\mathrm{g}\mathrm{k}+2\times \mathrm{l}\mathrm{o}\mathrm{g}\mathrm{L}\mathrm{\infty }$$

(2)

2.4. Mortality and Exploitation Rate

The length converted catch curve [59] was employed to estimate total mortality (Z).

Natural mortality (M) was calculated using the updated Pauly_nls-T estimator (Equation (3)) according to [60].

$$\mathrm{M}=4.118K^{0.73}\times {Linf}^{-0.33}$$

(3)

The total mortality rate (Z) was also computed using the Beverton & Holt empirical equation [61] (Equation (4)) to validate the Z estimate derived from the length-converted catch curve.

$$\mathrm{Z}=\mathrm{K}\times (\mathrm{L}\mathrm{\infty }-{\mathrm{L}}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}})/({\mathrm{L}}_{\mathrm{m}\mathrm{e}\mathrm{a}\mathrm{n}}-{\mathrm{L}}^{\prime })$$

(4)

where L_mean: the mean length of all fish in a sample representing a steady-state population, and L’: the cut-off length or the lower limit of the smallest length class included in the computation.

The annual fishing mortality rate (F) was obtained by subtracting Μ from Z, according to [62] (Equation (5)).

$$\mathrm{F}=\mathrm{Z}-\mathrm{M}$$

(5)

The exploitation rate (E), a measure of the number of fish that are caught from a population each year, was calculated as the ratio of F to Z [59] (Equation (6)).

$$\mathrm{E}=\mathrm{F}/\mathrm{Z}$$

(6)

The length class with the highest biomass (Le) (eumetric length) was calculated according to [63,64] (Equation (7)).

$$\mathrm{L}\mathrm{e}={\displaystyle \frac{3\times \mathrm{L}\mathrm{\infty }}{3+\frac{\mathrm{M}}{\mathrm{K}}}}$$

(7)

The length of first capture (Lc) for red mullet was determined as the size of the smallest individual caught. The probability of capture at 25% (L₂₅), 50% (L₅₀), and 75% (L₇₅) was estimated from the selectivity curve, constructed from the length-frequency data of captured fish [65]. Linear regression was applied to the ascending portion of the selectivity curve to derive these probabilities.

2.5. Relative Y/R and B/R Analysis: Knife-Edge Selection

The knife-edge method of Beverton and Holt’s yield-per-recruit (Y/R) model [61] (Equation (8)) was employed to assess the population dynamics of M. barbatus under varying fishing mortality (F) and exploitation rates (E). The model calculated Y/R and biomass-per-recruit (B/R) across a range of F (0.01 to 1.5) and E (0.01 to 1). Sensitivity to natural mortality was evaluated by computing Y/R and B/R for M adjusted by ±10%, similar to [22].

$${\displaystyle \frac{{\mathrm{Y}}^{\prime }}{\mathrm{R}}}=\mathrm{E}\times {\mathrm{U}}^{\mathrm{M}/\mathrm{K}}\times (1-{\displaystyle \frac{3\times \mathrm{U}}{\left(1+\mathrm{m}\right)}}+{\displaystyle \frac{3\times {\mathrm{U}}^2}{\left(1+2\mathrm{m}\right)}}+{\displaystyle \frac{{\mathrm{U}}^3}{\left(1+3\mathrm{m}\right)}})$$

(8)

where

$$\mathrm{U}=1-\left({\displaystyle \frac{{\mathrm{L}}_{\mathrm{c}}}{{\mathrm{L}}_{\mathrm{i}\mathrm{n}\mathrm{f}}}}\right)$$

$$\mathrm{m}={\displaystyle \frac{1-\mathrm{E}}{\frac{\mathrm{M}}{\mathrm{K}}}}=\mathrm{K}/\mathrm{Z}$$

All computations were performed in R (version 4.3.2) using the dplyr package [66], which facilitated data manipulation, creating data frames for F and E scenarios with B/R normalized for plotting. Reference points, including FMSY (fishing mortality at maximum sustainable yield), MSY (maximum sustainable yield), BMSY (biomass at MSY), and EMSY (exploitation rate at MSY), were identified.

3. Results

3.1. Population Structure

Red mullet accounted for 23% of the total abundance and 6.9% of the total weight (including both retained and discarded portions). Of the retained fraction, red mullet comprised 10.5% of the total commercial species weight landed, while it represented 3% of the total commercial species weight discarded.

On average, 46.22 ± 18 kg of commercial species was landed over the course of the study during each haul, with 39.14 ± 11.39 kg discarded on average. The red mullet’s weight landed during each haul was 4.78 ± 3.61 kg, with 1.17 ± 0.60 kg discarded on average (

Table 1. Descriptive statistics of the total commercial species and red mullets landed and discarded over 65 trawl surveys conducted between September 2022 and October 2024 in the region between Lesvos Island and Ayvalik.

	Mean	Median	Standard Deviation	Minimum	Maximum
Commercial Species landings (kg)	45.22	41.00	18.00	14.00	95.00
Commercial species discards (kg)	39.14	39.00	11.39	13.00	69.00
M. barbatus landed (kg)	4.78	4.50	3.61	0.30	14.00
M. barbatus discarded fraction (kg)	1.17	1.00	0.60	0.50	3.75

).

Of the M. barbatus individuals captured over the course of the study (3191 individuals), 15.6% (499 individuals) were discarded, and 84.4% were retained (3181 individuals). The length of discarded M. barbatus individuals was 6.52 ± 1.47 cm, whereas the retained fraction measured at 13.04 ± 2.32 cm (Figure 3) with significantly larger individuals retained (p < 0.001).

Net benefit analysis indicated that the depth range of 50–85 m was the optimal depth to fish when aiming for the highest M. barbatus landings and the worst was the 25–35 m depth range (Figure 4A), whereas the month with the highest M. barbatus landings was December, and the worst was October (Figure 4B).

Heatmaps of M. barbatus landings (Figure 5A) and discards (Figure 5B), expressed as CPUE (kg/h trawl) from the commercial trawls, revealed distinct spatial patterns. In Figure 4A, landings were characterized by two high CPUE “hotspots” located in the central-north and southeastern parts of the study area, connected by a less continuous band of elevated CPUE separated by areas of lower catches. In contrast, discards (Figure 4B) were more sparsely distributed, with modest peripheral peaks and without a strong spatial overlap with the landing hotspots, suggesting a spatial mismatch between the occurrence of smaller, discarded individuals and larger, retained fish.

3.2. Age Composition and Growth

Eight distinct age classes were identified (Figure 6).

The length at age population structure for M. barbatus exhibited a distribution where the population percentage peaked at age group 5, comprising 26.45% of the total, followed by a notable presence at age group 3 with around 23.9%. Age group 1 contributed 16.72%, while age groups 2, 4, and 6 each accounted for roughly 5–10%. The population diminished significantly in the older age groups, with age groups 7 and 8 each representing less than 5%. This structure indicated a population dominated by younger to middle-aged individuals (1–5), with a decline in both proportion and representation as the fish age and grow larger beyond age 5.

Asymptotic length (L∞) was estimated as 27.9 cm, and the growth coefficient (k) was estimated as 0.21 year⁻¹. The growth performance index (φ′) was estimated at 2.21, indicating a relatively slow growth rate.

3.3. Mortality and Exploitation Rate

Natural mortality (M) was estimated at 0.44, and total mortality (Z) was estimated at 1.18 using the length converted catch curve method (LCCC) and 1.21 using the Beverton–Holt (BH) equilibrium model (with L_mean and L′ at 14.43 cm and 12.1 cm, respectively). Fishing mortality (F) was estimated at 0.74. The exploitation rate (E), calculated as 0.63, indicates that the population is overexploited.

The length class with the highest biomass (Le) was estimated at 16.6 cm. The probability of capture was estimated at 25% (LC₂₅), 50% (LC₅₀), and 75% (LC₇₅) levels as 10.19, 10.92, and 11.46 cm, respectively (Figure 7). The age at which 50% of individuals are likely to be captured (t₅₀) was estimated to be 2.68 years.

3.4. Relative Y/R and B/R Analysis: Knife-Edge Selection

Figure 8 and Figure 9 illustrate the yield per recruit (Y/R) in relation to exploitation rate and fishing mortality, respectively, for varying levels of natural mortality.

Table 2. Values of parameters estimated in the study.

Symbol	Parameter Name	Estimated Value
L∞	Asymptotic length	27.9 cm
K	Growth coefficient	0.21 year−1
φ′	Growth performance index	2.21
M	Natural mortality rate	0.44 year−1
F	Fishing mortality rate	0.74 year−1
Z (LCCC)	Total mortality (length-converted catch curve)	1.18 year−1
Z (BH)	Total mortality (Beverton–Holt)	1.21 year−1
E	Exploitation rate	0.63
Le	Length at first capture	16.6 cm
LC50	Length at 50% gear selection	10.92 cm
t50	Age at 50% probability of capture	2.58 years
EMSY	Exploitation rate at maximum sustainable yield	0.64
MSY	Maximum sustainable yield	0.0272
BMSY	Biomass at MSY	0.0348
FMSY	Fishing mortality at MSY	0.78 year−1

summarizes the values of all parameters that were estimated in the study.

4. Discussion

4.1. Age Structure and Population Dynamics

The sustainable management of M. barbatus fisheries in the Eastern Aegean Sea is critical given the species’ ecological and economic importance in Mediterranean demersal fisheries. As a highly valued commercial species, the red mullet faces intense fishing pressure, necessitating robust stock assessments to inform effective conservation strategies. This study’s findings on population dynamics, including growth, mortality, and length-at-capture metrics, highlight the challenges of balancing exploitation with stock resilience, such as the high exploitation rate (E = 0.63) exceeding sustainable thresholds, the harvest of individuals below the optimal biomass size (LC₅₀ = 10.92 cm vs. Le = 16.6 cm), the low representation of older, reproductively valuable age classes, and the spatial mismatch between landing hotspots and areas with high discard rates. Reliable stock assessments and effective fisheries management depend fundamentally on accurate estimates of key life history traits, including age and growth (length-at-age), length at first sexual maturity, mortality rates, and variability in length-at-age within the population [67,68,69]. In addition, the uncertainties in the age data for red mullet are a challenge to the proper management of this important resource [70].

The age structure of M. barbatus in the Eastern Aegean Sea, as revealed by this study, provides useful insights into the population dynamics of this commercially significant species, with eight age classes identified and a peak abundance at age groups 3 (26.4%) and 5 (25%). This distribution, dominated by younger to middle-aged individuals, aligns with patterns observed in other Mediterranean and Black Sea studies, though variations exist due to regional differences in fishing pressure and environmental conditions. For instance, [18] reported a similar age structure in the North Aegean Sea, with a peak at ages 2–4, but noted a lower representation of older age groups (>6 years), likely due to higher fishing mortality. In contrast, Sieli et al. [19] found a broader age range in the Gulf of Castellammare, with a significant presence of age groups up to 7 years, attributed to a trawling ban that reduced fishing pressure. Yildiz and Karakulak [36] documented a dominance of age groups 1–3 in the western Black Sea, with fewer individuals reaching age 5, reflecting intense exploitation. These comparisons suggest that while the Eastern Aegean population maintains a relatively robust age structure, the scarcity of older age groups (>5 years) in this study indicates ongoing fishing pressure, necessitating management strategies to protect older, reproductively mature individuals [71,72]. It is well established that variations in age, growth, and mortality estimates can be influenced by a range of factors, including environmental conditions (e.g., temperature and salinity), habitat heterogeneity, latitudinal gradients, food availability, maturity stages, timing of fishing activities, sampling techniques, gear selectivity, and genetic differences among populations [73,74,75,76].

4.2. Growth Parameters and Comparative Analysis

When compared to studies conducted in Turkish waters after 2013, the current study reports among the highest asymptotic lengths (L∞ = 27.9 cm), indicating large potential size for M. barbatus in the sampled population. Studies by Aydın and Karadurmuş [77], Arslan and İşmen [17], and Onay et al. [78] reported similar L∞ values of 27.4 cm, 28.75 cm, and 28.19, respectively. Meanwhile, other studies, such as Çiloğlu and Akgümüş [79], Yildiz and Karakulak [36], and Kasapoğlu [80], documented lower L∞ values of 24.66 cm, 24.1 cm, and 24.6 cm for both sexes. These studies reported similar growth coefficients (k = 0.16–0.24 year⁻¹) to the current study’s k value of 0.21 year⁻¹. These small differences could be attributed to environmental, ecological, or density-dependent constraints [81]. The low growth coefficient observed may reflect a combination of life history strategy, environmental variability, and fishing pressure. Long-term changes in productivity, driven by climate and ecosystem variability, could influence growth rates, and future studies integrating multi-year environmental and biological datasets are recommended to investigate these dynamics.

Growth performance index (φ′) values from post-2014 studies in Turkish waters ranged between 1.99 and 2.32, with most studies, such as those by [17,36,79], reporting higher or equivalent φ′ values than the current study’s estimate of 2.21. Saglam [82], for example, presented a much smaller L∞ of 22.05 cm but a high k of 0.43 year⁻¹ and φ′ of 2.32, exemplifying a fast-growing, short-lived population. Collectively, these comparisons indicate that the studied red mullet population is characterized by a slow-growth, large-size life history strategy, which may have implications for stock resilience and management under continued fishing pressure. Specifically, such populations are generally more vulnerable to overfishing because they require longer periods to reach maturity and replenish biomass after depletion. This means that recovery from stock declines is slower, and sustainable exploitation requires more conservative harvest rates, larger minimum size limits, and protection of older, larger individuals to maintain reproductive output. Fish growth can vary due to factors like genetics, temperature, food availability, and diseases [83,84]. Additionally, population characteristics may fluctuate yearly due to factors such as inconsistent recruitment and changing environmental conditions [85]. A limitation of this study is the lack of sex-specific growth assessments, as sex was not evaluated due to the constraints of commercial sampling methods. This omission is important, given the documented differences in growth rates between male and female red mullet, with females typically exhibiting slower growth, larger sizes, and longer lifespans [36,77]. Addressing sex-specific growth in future studies will be crucial for a more comprehensive understanding of red mullet population dynamics and for informing effective stock management strategies under ongoing fishing pressure [23,86,87,88,89].

The von Bertalanffy growth function (VBGF) successfully characterized the growth of M. barbatus in the Eastern Aegean Sea, though its estimates may be affected by interannual growth variability due to sampling across four commercial trawling seasons. Environmental factors, such as temperature and prey availability, can cause annual variations in growth rates [75], potentially skewing VBGF parameters (L∞, k) and subsequent mortality estimates [60]. To mitigate this, future research should incorporate multi-season sampling and environmental covariates to enhance growth models and improve the accuracy of stock assessments in this dynamic region [90,91]. Additionally, studies on M. barbatus could explore reproductive biology, diet and feeding ecology, and habitat preferences. Examining recruitment dynamics and conducting socioeconomic assessments could further support adaptive and sustainable fisheries management [75,92].

4.3. Mortality, Exploitation Rate, and Stock Status

The stock assessment results for M. barbatus indicate that the population is currently under significant fishing pressure and is overexploited. Total mortality (Z) was estimated at 1.18 using the length-converted catch curve (LCCC) method and 1.21 via the Beverton-Holt (BH) equilibrium model. The minor discrepancy (~2.5%) reflects methodological differences: LCCC derives Z from the slope of the descending limb in length-frequency data, making it sensitive to selectivity and recruitment variation, while BH calculates Z from mean size (L⁻) under steady-state assumptions, potentially overestimating mortality if growth parameters are biased. The close agreement between estimates suggests consistent mortality signals, with LCCC preferred where growth parameters are robust and BH useful for equilibrium-based assessments. Natural mortality (M) was estimated at 0.44, and fishing mortality (F), at 0.74, exceeded natural mortality and accounted for most of the total mortality. The calculated exploitation rate (E = 0.63) surpassed the commonly accepted threshold of 0.5, indicating that the stock is exploited beyond sustainable biological limits [31]. Mehanna and Hassanien [93] examined M. barbatus in Egypt’s Nile Delta and reported a fishing mortality (F) of 1.18 year⁻¹ and an exploitation rate (E) of 0.65, supporting the outcomes of the present study. In the Western Black Sea, Yildiz and Karakulak [36] found F to be 0.86 year⁻¹, Z = 1.32 year⁻¹, and E = 0.65 based on age-structured methods, while length-based approaches yielded slightly higher values (F = 1.11 year⁻¹, Z = 1.57 year⁻¹, E = 0.71), suggesting overexploitation and minor methodological differences. Similarly, in Iskenderun Bay (Northeastern Mediterranean), Çiçek [94] reported F at 0.93 year⁻¹, Z at 1.39 year⁻¹, and E at 0.67. While total and fishing mortality rates tend to be elevated across these regions, the exploitation rates are consistently comparable to those observed in the present study.

These elevated fishing mortality and exploitation rates strongly indicate overfishing and can be attributed to several drivers. Intensive bottom-trawl fisheries remove large numbers of small and immature red mullet, exacerbated by gear selectivity that captures individuals before they reach reproductive size [71,95,96]. High fishing pressure, supported by evidence of exploitation rates consistently above 0.6 and fishing mortalities exceeding natural levels [89,93], leaves insufficient time for fish to mature and reproduce. Moreover, inadequate regulation and unreported catch (IUU fishing) are pervasive in the Mediterranean–Black Sea region, further driving down stock biomass [97,98], and escape mortality from gear results in unaccounted juvenile losses [99,100,101].

4.4. Gear Selectivity and Size at First Capture

The length class contributing the highest biomass (Le) was estimated to be 16.6 cm, yet the length at which 50% of individuals are vulnerable to capture (LC50) is only 10.92 cm. This discrepancy suggests that fish are being harvested before reaching their optimal biomass, limiting their contribution to reproduction and future stock growth. The length at first capture, Lc, was estimated at 11.76 and 11.54 cm TL for males and females according to Mehanna and Hassanien [93]. Yildiz and Karakulak [36] estimated the LC at 8.8 cm. The differences in the estimated length at first capture (Lc) could be attributed to variations in fishing gear selectivity, sampling methodologies, and environmental conditions across study regions [102,103,104]. Length at first maturity for females and males has been reported at 11.9 cm and 12.1 cm, respectively, in Saros Bay (North Aegean Sea) [17]; 12.40 cm and 11.29 cm for females and males, respectively, in the Black Sea [105]; 11.4 cm for females in north Aegean Sea [106]; and 13.87 cm for males and 13.94 cm for females in the Gulf of Tunis [89]. Differences in gear types, such as mesh sizes or trap designs, can significantly affect the size at which fish are captured, with smaller mesh sizes typically catching smaller individuals [107,108]. Additionally, spatial and temporal variations in fish population dynamics, including growth rates and habitat-specific factors, may influence Lc estimates [109]. Discrepancies in sampling techniques, such as the choice of sampling sites or seasons, could further contribute to these differences [110]. These factors highlight the importance of standardizing methodologies for accurate comparisons across studies.

4.5. Management Implications and Recommendations

Relative yield-per-recruit (Y/R) and biomass-per-recruit (B/R) analyses provide additional insights into the stock’s exploitation status. The fishing mortality that produces the maximum sustainable yield (FMSY) was estimated at 0.78, and the current F of 0.74 is very close to this level. Similarly, the exploitation rate at MSY (EMSY) was 0.64, almost equal to the current exploitation rate of 0.63. While this suggests that the fishery is operating near the point of maximum sustainable yield, the proximity to these reference points indicates minimal room for error or additional pressure. Small increases in fishing effort or recruitment fluctuations could push the stock into an overfished state with declining yields and biomass. Given these findings, precautionary fishery management measures are strongly recommended. First, fishing mortality should be reduced to levels below FMSY, ideally to F ≤ 0.7, to create a buffer for stock recovery and account for uncertainty in estimates. Second, measures should be taken to increase the length at first capture, shifting LC50 closer to the optimal biomass size of 16.6 cm. This could be achieved by regulating gear selectivity, such as increasing mesh size [61,111]. Additionally, effort controls (e.g., limiting fishing days or fleet capacity), seasonal or area closures to protect spawning aggregations, and science-based catch limits (TACs) aligned with MSY estimates should be implemented as part of a precautionary management framework [112,113]. Continuous monitoring and regular reassessment are also necessary to evaluate stock trends and adapt management strategies based on updated biological and fishery data [92,114]. Overall, the current indicators signal that M. barbatus is being harvested at unsustainable levels, and immediate management actions are needed to ensure the long-term health and productivity of the population.

The net benefit analysis for M. barbatus in the Eastern Aegean Sea, calculated as the difference between retained and discarded biomass, revealed that the 50–85 m depth range yielded the highest net benefit, indicating it as the optimal depth for maximizing landings while minimizing discards, whereas the 25–35 m range was the least productive. Seasonally, December showed the highest net benefit, contrasting with October as the least favorable month. These findings suggest that targeting deeper waters (50–85 m) and fishing in December could enhance fishery efficiency by increasing the retention of commercially valuable red mullet while reducing the discard of smaller, non-marketable individuals. This spatial and temporal variation likely reflects ecological factors such as habitat preferences, spawning aggregations, or seasonal migrations, emphasizing the need for depth- and season-specific management strategies to optimize yield and support sustainable fishing practices. These findings align with other studies, such as a 2015 deep-sea fishery analysis recommending a 600 m depth limit to reduce discards and enhance catch value [115], and a Namibian hake fishery study showing that depth-based restrictions skew catches toward deeper species, impacting net benefits and stock recovery [116]. These patterns suggest that depth and seasonal variations significantly influence fishery efficiency, with deeper waters and specific months like December optimizing economic returns for M. barbatus by targeting larger, marketable fish. Given the species’ overexploited status (exploitation rate E = 0.63), management strategies should integrate depth-specific fishing (50–85 m), seasonal targeting (e.g., December), and gear modifications to increase length at first capture (LC50 = 10.92 cm) closer to the optimal biomass size (Le = 16.6 cm), ensuring sustainability.

4.6. Spatial and Seasonal Fishing Patterns

Heatmaps of M. barbatus landings and discards from the trawl surveys showed distinct spatial patterns implying selective trawling strategies to maximize landings and minimize discards, possibly influenced by regulations, economics, or habitat preferences, with smaller (discarded) individuals and adults occupying different zones. The high discard rate of M. barbatus observed in the present study, with 15.6% of captured individuals (499 out of 3191) discarded due to their small size (mean length 6.52 ± 1.47 cm), reflects significant fishing pressure and inefficiencies in gear selectivity. This aligns with findings from Cerim et al. [34], who reported substantial discard rates in Southern Aegean trawl fisheries, driven by the capture of undersized red mullet before they reach reproductive maturity. The low length at first capture (LC50 = 10.92 cm) compared to the optimal biomass length (Le = 16.6 cm) indicates that juvenile fish are frequently caught, reducing reproductive potential and stock sustainability [71]. Such high discard rates are exacerbated by inadequate mesh sizes and intense bottom-trawl activities, which non-selectively capture small individuals, as noted by [95]. Implementing larger mesh sizes and seasonal closures, as suggested by [117], could mitigate discards, protect juvenile fish, and enhance the sustainability of M. barbatus fisheries.

4.7. Study Limitations and Future Research Directions

The present study has several limitations that should be considered when interpreting the results. First, sex-specific growth data were not collected due to the constraints of commercial sampling methods, preventing assessment of potential differences in growth, size-at-maturity, and longevity between males and females, a factor known to influence stock dynamics in Mullus barbatus. Second, the study did not incorporate otolith-derived age data, which are generally considered more accurate for ageing demersal species than length-frequency methods. Although the Bhattacharya and ELEFAN approaches provide robust estimates in data-limited contexts, the absence of direct ageing validation may introduce uncertainty in growth and mortality parameters. Third, environmental variables such as temperature, salinity, substrate type, and prey availability, which can strongly influence growth, distribution, and CPUE, were not included due to the absence of concurrent, high-resolution environmental datasets for all sampling periods. Fourth, the temporal scope of the study was limited to four fishing seasons, with sampling concentrated in specific months, which may not fully capture seasonal and interannual variability in growth, recruitment, and spatial distribution. Finally, the study relied on fishery-dependent data from a single commercial trawler, which, while valuable for reflecting real-world fishing practices, may limit the spatial and methodological representativeness of the results.

Future research should build upon these findings by incorporating sex-specific biological data, otolith-based age determinations, multi-season and multi-year sampling, and integration of environmental covariates into spatial and growth models. The inclusion of reproductive biology studies, covering spawning seasonality, fecundity, and size-at-maturity, would provide critical inputs for refining biological reference points. Expanding sampling to include multiple vessels and gear types would improve representativeness and reduce potential biases from a single-platform dataset. In addition, coupling fishery-dependent data with fishery-independent surveys and electronic monitoring could enhance accuracy in catch and discard estimates. Finally, linking spatial CPUE patterns to environmental and habitat variables would allow for predictive modeling of distribution shifts under changing oceanographic conditions, supporting adaptive and ecosystem-based fisheries management for M. barbatus in the Eastern Aegean Sea.

These insights underscore the importance of aligning fishing practices with ecological and biological data to enhance net benefits while mitigating overexploitation. The spatial and temporal patterns observed in the Eastern Aegean Sea, coupled with comparable findings from deep-sea and Namibian fisheries, highlight the need for adaptive management strategies. Implementing depth restrictions, seasonal closures, and improved gear selectivity can reduce discards and protect juvenile fish, supporting stock recovery [117,118,119,120,121]. Additionally, the study by Bertelsen et al. [122] emphasizes electronic monitoring (EM) and fully documented fisheries (FDF) as innovative solutions to enhance data collection, reduce discards, and improve compliance with regulations, offering a pathway to sustainable management of overexploited species like M. barbatus (exploitation rate E = 0.63). Implementing EM and FDF provides real-time catch and discard data, enabling adaptive management to protect juvenile fish and enforce depth and seasonal restrictions. Nevertheless, continuous monitoring and incorporation of environmental covariates are critical to refining these approaches and ensuring the long-term viability of M. barbatus and similar fisheries under intense fishing pressure.

5. Conclusions

This study provides compelling evidence that the red mullet (M. barbatus) population in the Eastern Aegean Sea is currently experiencing biologically unsustainable levels of exploitation. The high exploitation rate (E = 0.63) and fishing mortality (F = 0.74), which approaches the estimated FMSY threshold (0.78), underscore the urgent need for precautionary, science-based management measures. The dominance of younger age classes (3–5 years old) and the scarcity of older, reproductively valuable individuals indicate persistent fishing pressure that is likely constraining reproductive potential and long-term stock viability. Furthermore, the current length at 50% capture (LC50 = 10.92 cm) is well below the optimum length for biomass (Le = 16.6 cm), suggesting that fish are being caught before they can contribute meaningfully to stock replenishment. In light of these findings, reducing fishing mortality to levels below FMSY, ideally to F ≤ 0.70, would help create a buffer for stock recovery and account for uncertainty in estimates. Increasing the length at first capture toward the optimal biomass size could be achieved by regulating gear selectivity, while effort controls, seasonal or area closures to protect spawning aggregations, and science-based catch limits aligned with MSY estimates would further support sustainability. Continuous monitoring, the integration of electronic reporting or monitoring systems, and regular reassessment of stock status will be essential to adapt management strategies as conditions change. Without such timely interventions, the continued overharvesting of this valuable species risks irreversible population declines and significant socioeconomic repercussions for the fisheries dependent on it.