Assessment of Exploited Stock and Management Implications of Kingfish (Scomberomorus commerson) in the Omani Waters

Abstract

The high demand and economic value of kingfish (Scomberomorus commerson) have led to intensive fishing of this species in the Omani waters. The increased fishing pressure has made the fishery vulnerable; hence, information on the current stock status is essential for the sustainability of the kingfish stock. Three length-based stock assessment approaches (TropFishR, spawning potential ratio, and Bayesian biomass method) were used to estimate growth, mortality, exploitation, spawning potential capacity, and relative biomass in relation to maximum sustainable yield (MSY). Asymptotic length (L_∞) was 186.31 cm, and the growth coefficient (K) was 0.15 yr⁻¹ for S. commerson. Fishing mortality was 0.45 yr⁻¹, which was higher than natural mortality (M = 0.18 yr⁻¹) and optimal fishing mortalities (F40% = 0.15 yr⁻¹). The exploitation rate (E) was found to be 0.71 yr⁻¹, higher than the optimum exploitation (E = 0.50), indicating a total overfishing of 42% of the S. commerson in Oman waters. The current length at first capture (Lc50 = 74.38 cm) was significantly smaller than the length at first maturity (Lm50 = 91.25 cm), indicating growth overfishing. The current spawning potential ratio (SPR) was 10%, which was significantly below the reference point (SPR = 20%), indicating that the stock was severely overfished. Biomass was critically low (B/Bo = 0.17), and lower than the reference point of 0.20. Additionally, the current biomass was 44% of Bmsy (B/Bmsy = 0.44), which is significantly lower than the reference point of 1, indicating that the stock biomass was below the maximum sustainable yield level, suggesting recruitment overfishing. Stock indicators revealed that the fishery was primarily targeting immature/juvenile fish, as well as older and larger fish, which indicated stocks were both growth- and recruitment-overfished. Therefore, carrying out commercial fishing for an optimum size range (118 to 144 cm) and reducing fishing pressure to a sustainable level (F = M, 0.18 ^yr−1) would sustain a healthy stock biomass of kingfish in Omani waters.

1. Introduction

Kingfish, or narrow-barred Spanish mackerel (Scomberomorus commerson), is one of the valuable fish species in Oman, locally known as ‘Kanaad’. It is an epipelagic predator which is distributed widely from shallow coastal waters to the edge of the continental shelf, where it is found at depths of 10–70 m and capable of long migration [1]. It migrates from the Arabian Sea to the Arabian Gulf through the Sea of Oman to spawn. The kingfish juveniles return to the Sea of Oman and to the Arabian Sea for feeding and growth [2]. Genetic studies on S. commerson showed there were slight genetic differences among the stock in Djibouti, Oman, and the U.A.E [3].

Kingfish is one of the essential species in Oman for traditional fisheries. The catches decreased by 19.4%, from 2601 tons in 2018 to 2098 tons in 2019 [4]. The total value of kingfish landed in Oman was Rial Omani (R.O.) 18,432,000 (USD 47.9 million) in 2016 and decreased to R.O. 5,687,000 (USD 14.7 million) in 2019 [4] due to reduced landings. The catching and selling of kingfish have been banned for two months by the Ministry of Agriculture, Fisheries & Water Resources starting from 15 August of each year.

The length-based Bayesian (LBB) approach generates estimates of relative biomass indicators such as B/B₀ and B/BMSY, which serve as measures of a stock’s biological condition and sustainability [5]. This method applies Bayesian statistical modelling to derive biomass and fishing mortality estimates directly from length–frequency data, while effectively integrating prior information and accounting for uncertainty in parameter estimation [5].

The TropFishR package version 1.6.4 serves as an important tool for fisheries research, enabling analyses that rely on length–frequency information. It incorporates multiple techniques for stock assessment, making it especially advantageous for situations where detailed or extensive data on fish populations are lacking [6]. The TropFishR package builds upon the foundations laid out in the FAO Manual “Introduction to Tropical Fish Stock Assessment” along with several contemporary approaches [7,8]. By utilizing length–frequency datasets, it enables researchers to estimate key population dynamic parameters, including growth rate, mortality, exploitation levels, stock biomass, and management reference points. These features collectively contribute to more accurate stock evaluations and promote sustainable fisheries management practices [6].

Heavy exploitation of the kingfish stock has raised concerns about possible growth overfishing and recruitment failure in the RECOFI (Regional Organization for the Protection of the Marine Environment) sea areas [9]. Rapid growth of S. commerson juveniles from Oman, South Africa, and Australia, despite variations in growth estimates between locations, is observed, consistent with age-based growth [9]. The stock of S. commerson in the Sultanate of Oman waters is overexploited [2,10]. The population dynamics of this species covering parameters such as age, growth, mortality, and yield per recruit have been examined in various marine regions, including the Arabian Sea, Oman Sea, Arabian Gulf, and Persian Gulf [2,10,11,12]. Various aspects of its population dynamics and stock assessment are reported based on otoliths [2,9,10,13]. Bertignac and Yesaki [14] reported an increase in the minimum length limit of Omani S. commerson based on yield-per-recruit (Y/R) analysis. However, updated reports are not available on stock status and spawning biomass, which are essential for sustainable management implications of S. commerson in Omani waters.

To provide a comprehensive assessment of Scomberomorus commerson stock in Omani waters, a multi-model approach was employed. Three complementary length-based assessment methods were applied: TropFishR, the length-based spawning potential ratio (LBSPR), and the length-based Bayesian biomass (LBB) method. TropFishR is particularly useful for estimating growth parameters and mortality rates, LBSPR allows evaluation of reproductive potential and spawning stock status, and LBB provides insights into relative biomass and exploitation levels. Combining these models provides a more robust and integrated understanding of stock status, as each method addresses different aspects of population dynamics.

2. Materials and Methods

2.1. Study Area and Data Collection

Monthly fork length and weight data of Scomberomorus were collected from January to December 2019. A total of 1748 specimens were collected from six regions of the Sea of Oman and the Arabian Sea with the help of fishermen using hand lines and gillnets; few samples were captured by beach seines (Figure 1), ranging in size from 24 to 176 cm. The S. commerson catch from each landing site was weighed. The sample was measured using biometric measurements, including fork length (FL) and total weight (TW) using the electronic scale to the nearest 0.5 kg. Additionally, the total and standard lengths were measured to the nearest 1 cm using a 200 cm measuring rope at the markets and landing sites.

Figure 1. Location of the six regions where Scomberomorus commerson were sampled in the coastal waters of Oman. Black areas indicate the extent of the fishing grounds for each region.

2.2. Assessment Models

2.2.1. Length–Weight Relationship

The length–weight relationship (LWR) was determined using the following equation [15]:

W = aL^b

where a is a constant, b is the relative growth coefficient, L is the fork length (cm), and W is the weight of the kingfish (g). The 95% confidence interval of b was estimated based on Sparre and Venema [7].

2.2.2. Growth Parameters

The growth parameters, including the asymptotic length (L_∞) and the growth coefficient (K), were estimated using the Von Bertalanffy Growth Function (VBGF) [7]:

$${\mathrm{L}}_{\mathrm{t}}={\mathrm{L}}_{\mathrm{\infty }}\left[1-{\mathrm{e}}^{-\mathrm{K}(\mathrm{t}-{\mathrm{t}}_0)}\right]$$

where Lt represents the fork length at age t, L_∞ denotes the asymptotic fork length (in cm), K is the growth rate (year⁻¹), and t₀ is the point in time when the kingfish has zero length [16]. Estimation of the t₀ parameter was determined by the empirical equation proposed by Pauly [17]:

Log (−t₀) = (−0.3922) − 0.2752 log (L_∞) − 1.038 log (K)

2.2.3. Mortalities and Exploitation

The total mortality (Z) was estimated using the length-converted catch curve approach available in the TropFishR package. The natural mortality (M) was then calculated by employing an empirical equation developed by [18].

M = 4.118 × K^0.73 × L_∞^−0.33

Subsequently, fishing mortality (F) was determined using the equation F = Z − M, where Z represents total mortality and M denotes natural mortality. The exploitation rate (E) was then computed using the formula E = F/Z [19].

2.2.4. Yield per Recruitment

A yield-per-recruit (YPR) analysis utilizing length-based data was performed using the Thompson and Bell model within the TropFishR package [6] to assess the population status of Scomberomorus commerson and identify benchmarks for sustainable fishery practices. This evaluation incorporated key biological inputs, including mortality estimates, growth parameters derived from the Von Bertalanffy model, length–frequency data, and length–weight correlations. The calculated fishing mortality (F) was then compared against several biological reference points to gauge its impact on the stock. These benchmarks included F_0.1, indicating 10% of the initial slope of the YPR curve; F_0.5, the level at which spawning biomass is reduced to half of its original state; F_0.4, corresponding to a spawning potential ratio (SPR) of approximately 40%; and Fmax, the fishing mortality rate that produces the highest yield per recruit.

2.2.5. Length-Based Spawning Potential Ratio (LBSPR)

The length-based spawning potential ratio (LBSPR) approach is extensively used for assessing fish stocks, particularly in fisheries with limited data availability. It estimates the spawning potential ratio (SPR), a key biological reference point for evaluating the status and sustainability of fish populations [20]. In unfished populations, SPR equals 1, indicating full reproductive capacity, while an SPR of 0 reflects complete reproductive failure [20]. An SPR value of around 0.4 is typically associated with maximum sustainable yield (MSY), whereas values below 0.2 suggest poor recruitment and potential recruitment overfishing [21]. The LBSPR model incorporates several essential biological and growth parameters, including asymptotic length (L_∞), the M/K ratio, length–weight relationship coefficients (a and b), and maturity indicators such as length at 50% maturity (Lm50) and length at 95% maturity (Lm95) [22]. Lm50 and Lm95 of the Scomberomorus commerson were calculated by using the following equations [23]:

Log Lm50 = 0.8979 × Log L_∞ − 0.0782
Lm95 = 1.1 × Lm50.

The LB-SPR R package [24], available at https://CRAN.Rproject.org/package=LB-SPR and accessed in 5 September 2024, was used to estimate SPR.

2.2.6. Length-Based Bayesian Biomass (LBB)

The Length-based Bayesian Biomass (LBB) approach [6] assesses the status of fish stocks using three principal indicators: the biomass at maximum sustainable yield (B/BMSY), the ratio of current to unexploited biomass (B/B0), and the ratio of fishing mortality to natural mortality (F/M). A B/B_MSY value greater than 1 signifies that the stock is underexploited, while values between 0.8 and 1.0 indicate a fully exploited stock. Conversely, when B/BMSY is below 0.8, the population is considered overexploited [5,25]. Moreover, a B/B0 ratio less than 0.5 also reflects overexploitation, as does an F/M ratio exceeding 1, both of which imply excessive fishing pressure [6]. The optimal values for the ratios L_mean/L_opt (mean length of captured fish to optimal harvest length) and Lc/Lcopt (length at first capture to optimal length at first capture) are typically equal to 1. Ratios below 1 suggest growth overfishing or excessive harvesting of juvenile individuals.

The LBB analysis was implemented using the LBB package in R [6], available at https://www.Cran.Rproject.org/package=LBB; accessed in 5 September 2024. Key input parameters used in this analysis included the asymptotic length (L_∞), the M/K ratio, length at 50% capture (Lc50), and length at 50% maturity (Lm50). The Lc50 value was determined through a length-converted catch curve analysis, employing the “calc_ogive” function in the TropFishR package.

$${\mathrm{L}}_{\mathrm{opt}} (\mathrm{length} \mathrm{at} \mathrm{optimal} \mathrm{yield}) \mathrm{was} \mathrm{estimated} \mathrm{as} {\mathrm{L}}_{\mathrm{opt}}={\mathrm{L}}_{\mathrm{\infty }}({\displaystyle \frac{3}{3+\frac{\mathrm{M}}{\mathrm{k}}}}).$$

where ${\mathrm{L}}_{\mathrm{\infty }}$ is the asymptotic length, $\mathrm{M}$ is the natural mortality, and $\mathrm{k}$ is the growth coefficient. This formula was adapted from [26]. The Lopt range was defined as ±10% of the estimated Lopt, and individuals exceeding this range were classified as mega spawners [26]. The detailed description of the LBB method is provided in [5].

3. Results

3.1. Length–Weight Relationship

A total of 1748 specimens were collected, with total lengths ranging from 24 cm to 176 cm. The length–weight relationship was determined for 805 samples of S. commerson. The relative growth coefficient (b) was less than 3 with a 95% confidence interval of b between 2.56 and 2.68. Therefore, the relative growth of S. commerson was negative allometric in the investigated areas. The length–weight relationship model of S. commerson was W = 0.0388L^2.62 and R² = 0.90 (Figure 2).

Figure 2. Length–weight relationship of S. commerson in the coastal water of Oman.

3.2. Growth Parameters

The ELEFAN-GA approach available in the TropFishR package was applied to estimate the Von Bertalanffy Growth Function (VBGF) parameters, including the asymptotic length (L_∞) of 186.31 cm and the growth coefficient (K) of 0.15 ${\mathrm{y}\mathrm{r}}^{-1}$ for S. commerson (Table 1). The theoretical age when S. commerson reached zero length (t0) was −0.0152. The Von Bertalanffy Growth Function (VBGF) for Scomberomorus commerson was defined as Lt = 185.85 (1 − e^{−0.15(t+0.015)}). The fitted growth curve was overlaid on the restructured length–frequency histograms (Figure 3). The growth performance index (φ’) for S. commerson in this study was calculated to be 3.76. The observed maximum length was 176 cm, and the predicted maximum length was 186 cm. The confidence interval was 168–205 cm (95% probability of occurrence). The maximum age (tmax) of the S. commerson in the Omani waters was 22 years. The smallest length of S. commerson was 24 cm, captured by beach seines.

Table 1. Overview of the population characteristics of Scomberomorus commerson in Omani coastal waters.

Population Parameter	Estimated Value
Sample size (n)	1748
Asymptotic length (L∞, cm)	186.31
Growth performance index (Φ’)	3.76
Growth coefficient, K (yr−1)	0.15
Hypothetical age (t0, yr)	−0.015
Total mortality (Z, yr−1)	0.63
Natural mortality, M (yr−1)	0.18
Fishing mortality, F (yr−1)	0.45
Exploitation rate, E (yr−1)	0.71
Length at 50% maturity (Lm50, cm)	91.25
Length at 95% maturity (Lm95, cm)	100.37
Length at first capture (Lc50, cm)	74.38
Length–weight relationship intercept (a)	0.0388
Relative growth coefficient (b)	2.26

Figure 3. A length–frequency histogram was generated using the bootstrapped ELEFAN-GA method with an appropriate moving average for Scomberoides commersonnianus. This was overlaid on the restricted length–frequency distributions. In the plot, black and white bars indicate positive and negative deviations, respectively, from the weighted moving average of three consecutive length classes, illustrating the presence of pseudo-cohorts within the population.

3.3. Mortalities and Exploitation

The total mortality (Z) was calculated to be 0.63 yr⁻¹ using the length-converted catch curve (Figure 4). The natural mortality (M) was estimated at 0.18 yr⁻¹, and the fishing mortality (F) was determined to be 0.45 yr⁻¹. The F/M ratio was 2.50, exceeding the reference value of 1, which indicates intense fishing pressure and an unbalanced stock. Additionally, the exploitation rate (E) was determined to be 0.71 yr⁻¹, surpassing the optimal threshold of 0.50, suggesting that Scomberomorus commerson in Omani waters is experiencing approximately 42% overexploitation.

Figure 4. Length-converted catch curve of the S. commerson in the Omani waters. Black circles are lines used to estimate the total mortality (Z). The white circles are the fish that were not recruited to the fishing gear; thus, they were not selected to estimate the total mortality.

3.4. Size Structure, Length at First Capture, and Length at Maturity

Length at first capture (Lc50%) was found to be 74.38 cm, while age at first capture (t50) was 3.39 years (Figure 5). The mean fork length of S. commerson was estimated as 91.26 cm. The length–frequency distribution over 12 months suggested that the mean fork length of S. commerson was 91.26 cm, with the highest abundance in the 89–95.5 cm length range (Figure 6). The length at 50% capture (Lc50) of 74.38 cm was lower than the length at 50% maturity (Lm50) of 91.25 cm, indicating growth overfishing for S. commerson in Omani waters (Figure 6).

Figure 5. The probability of selectivity of S. commerson in Omani waters is the age at t50, which is the age at which the gear catches 50% of the fish.

Figure 6. Length–frequency distribution of S. commerson in the coastal water of Oman in relation to the Lc₅₀ (length at 50% capture), Lm₅₀ (length at 50% maturity), L_opt range (optimum length range), and L_∞ (asymptotic length).

3.5. Yield per Recruitment

The yield-per-recruit (YPR) model was used to determine the biological reference points for Scomberomorus commerson inhabiting the Omani coastal waters. The estimated parameters included F_max = 0.30 year⁻¹, representing the fishing mortality rate that yields the maximum output per recruit; F_0.5 = 0.11 year⁻¹, the rate at which the spawning biomass is reduced to half of its virgin level; and F_0.1 = 0.16 year⁻¹, indicating the point where the slope of the yield-per-recruit curve is 10% of its initial slope (Table 2; Figure 7).

Table 2. Reference points and current fishing mortality against yield per recruit for S. commerson in the coastal waters of Oman.

Fishing Mortality (yr−1)	Yield per Recruit (g/Recruit)
F0.1 = 0.16	2599.01
F0.5 = 0.11	2308.82
Fmax = 0.30	2800.90
Fcurrent = 0.45	2734.87

Figure 7. Thompson and Bell model illustrating the yield-per-recruit and biomass-per-recruit curves. The green, yellow, and red lines correspond to the F_0.5, F_0.1, and F_max reference points, respectively, while the black line denotes the current fishing mortality rate for Scomberomorus commerson in Omani waters.

The analysis showed that the current fishing mortality (F = 0.45) surpasses both F_0.5 and F_0.1, suggesting that S. commerson in Omani waters is undergoing growth overexploitation. Furthermore, the current yield per recruit was found to be 2734.87 g/recruit (Figure 8), which is slightly higher than the value associated with F_0.5 (Table 2), reinforcing evidence of excessive fishing pressure on this stock.

Figure 8. The isopleth of yield per recruit concerning different fishing mortality and length at first capture. The black dot represents the current yield per recruit in relation to current fishing mortality and current Lc50 for S. commerson in the coastal water of Oman.

3.6. Length-Based Spawning Potential Ratio (LB-SPR)

The results of the length-based spawning potential ratio (LB-SPR) are shown in Table 3 and Figure 9. The current spawning potential ratio (SPR) was 10%, which is significantly below the reference point (SPR = 20%), indicating that the stock was severely overfished. The fishing mortality was extremely high, indicated by an F/M ratio of 2.73, which shows that fishing mortality was 2.73 times greater than natural mortality. The level of fishing pressure was extremely high, significantly contributing to the lower SPR. A balanced F/M ratio is often near one or below, depending on the life history of the fish species and management goal. The selectivity parameters indicate that 50% of the fish were vulnerable to the fishing gear at a length of 76.42 cm (SL50), and 95% of the fish were vulnerable at a length of 105.18 cm (SL95). When compared to the maturity parameters, such as Lm50 at 81.57 cm and Lm95 at 92.61 cm, it is revealed that a significant portion of the fish were caught before they reached maturity, reducing their chances of reproducing. With an asymptotic length (L_∞) of this fish of 186.31 cm, the stock has the potential to grow much larger, but current fishing practices are removing fish too early in their life cycle. These findings underscore the urgent need for management interventions to reduce fishing mortality, protect immature fish, and enable the population to recover to a sustainable level.

Table 3. Results of the LB-SPR for S. commerson in the coastal water of Oman.

Parameters	Value	Interpretation
Spawning potential ratio (SPR)	0.10 (10%)	SPR > 40% indicates a healthy stock (target level); SPR ≈ 20% is the limit reference point (values below this indicate overfishing); SPR < 10–20% suggests severe overfishing.
F/M	2.73	F/M = 1 suggests optimum fishing pressure in the population.
SL50%	76.42 cm	Estimated SL50% was lower than length at 50% maturity (SLm50 = 91.25 cm).
SL95%	105.18 cm	Estimated SL95% was lower than length at 90% maturity (SLm50 = 100.37 cm).

Figure 9. The result of the LBSPR model of S. commerson in the coastal water of Oman: (A) size–frequency distribution, (B) curve of maturity and selectivity, (C) the current SL50%, SL95%, F/M, and SPR, (D) the sampled fish size against the targeted size class to achieve target SPR of 40% based on the current observed size–frequency data.

3.7. Length-Based Biomass (LBB)

The results for the LBB are shown in Table 4 and Figure 10. The fishing mortality is nearly twice the natural mortality (F/M = 1.93), exceeding the population’s growth rate (F/K = 2.01) and suggesting unsustainable harvest rates. Biomass is critically low, with the current level at just 17% of the unfished state (B/Bo = 0.17), which is lower than the reference point of 0.20 (20%), suggesting that the stock has critically declined by 83%. Additionally, the current biomass is 44% of Bmsy (B/Bmsy = 0.44), which is significantly lower than the reference point of 1, indicating that the stock biomass is below the maximum sustainable yield level and is experiencing recruitment overfishing. The fish are being caught at a younger age and smaller size than is optimal, with the mean length (Lmean) at only 77% of the optimal harvest length (Lopt), and length at first capture (Lc) just 67% of the recommended Lcopt, which are strong indicators of growth overfishing. The estimated ${\mathrm{L}}_{\mathrm{opt}}value$ is 131 cm, with a range of 117.9–144 cm (Figure 6).

Table 4. Summary of the results of the length-based Bayesian biomass model for S. commerson in the coastal water of Oman.

Indicator	Value (CI)	Interpretation
B/Bo	0.17 (0.13–0.22)	Current biomass (B) is only 17% of unfished (virgin) biomass (Bo). This indicates heavily depleted stock. (B/B0 > 0.5) suggests the stock is in good condition (≥50% of unfished biomass, and B/B0 < 0.20 suggests the stock is critical).
B/Bmsy	0.44 (0.33–0.57)	Biomass (b) is 44% of biomass at maximum sustainable yield (Bmsy). Values < 1 suggest the stock is below sustainable biomass level (B/Bmsy = 1 suggests the stock is optimally exploited; B/Bmsy < 1 suggests the stock is overfished).
Lopt	131 cm	Optimum length for harvest to maximize yield and sustainability.
F/M	1.93 (1.57–2.36)	Fishing mortality (f) is 1.93 times higher than natural mortality (m). Values > 1 suggest high fishing pressure.
F/K	2.01 (1.79–2.28)	Fishing mortality (F) is 2 times higher than growth rate (K). This indicates extreme fishing relative to growth potential. F/K > 1 suggests that fishing rate exceeds population recruitment.
Z/K	3.04 (2.8–3.3)	Total mortality (z) is 3 times higher than growth rate (k). The high value confirms elevated mortality, mostly due to fishing.
L95th/ L∞	0.86	The 95th percentile of observed length is 86% of the asymptotic length. This is moderately good, and indicates some large fish are still present.
Lmean/Lopt	0.77	Mean length is 77% of optimum length. Values < 1 indicate that fish are being caught before reaching optimum size.
Lc/Lcopt	0.67	Length at first capture is 67% of optimum length at capture. This suggests that too many small fish are being caught.

Figure 10. Length-based Bayesian biomass output of S. commerson in the Omani coast. The left curve shows the model fits to the length data, while the right curve displays the predictions of the LBB method. Lc is the length at which 50% of the fish population is susceptible to capture by fishing gear. Linf is the asymptotic length, and Lopt is the length where the maximum biomass of the unexploited stock is obtained.

4. Discussion

4.1. Growth Parameters

Information on stock characteristics is a crucial component for the long-term, sustainable management of fisheries resources [27]. The growth parameters of S. commerson obtained in the present study show differences across various geographical locations worldwide (Table 5). The highest value of L_∞ (232.40 cm) is from Omani waters [13], and the lowest value (137.6 cm) is in Indian waters [28]. The value of K is observed in Iranian waters [11]. The lowest (0.17 ${\mathrm{y}\mathrm{r}}^{-1}$) value of K is observed in this study. The current L_∞ (186.31 cm) of S. commerson a higher than the values reported by McIlwain et al. [10] and Jayabalan et al. [2]. However, it is lower than the values reported in two other reports [9,13] in the coastal waters of the Sultanate of Oman (Table 5). The estimated K value was 0.15 yr^−1, which is close to other studies in the Omani waters, except the report (K = 0.40 yr⁻¹) of Jayabalan et al. [2]. Variations in sample size, timing of data collection, environmental conditions, fishing methods, and geographic locations could explain these differences [29].

Table 5. Growth parameters of S. commerson from different countries.

Country/Region	L∞ (cm)	$\mathbf{K} \mathbf{(}{\mathbf{y}\mathbf{r}}^{-1}$)	φ′	Source
Oman	186.31	0.15	3.76	Present study
Oman	226.0	0.21	-	Dudley et al., 1992 [28]
Oman	232.40	0.21	4.10	Al-Hosni & Siddeek, 1999 [13]
Oman	144.40	0.21	3.70	Mcllwain et al., 2005 [21]
Oman	176.00	0.40	4.09	Jayabalan et al., 2011 [30]
Iran	151.20	0.46	4.02	Kaymaram et al., 2013 [7]
Iran	140.00	0.42	3.91	Shojaei et al., 2007 [31]
United Arab Emirates	138.60	0.21	3.60	Grandcourt et al., 2005 [23]
Queensland	141.25	0.20	3.60	Sumpton & O’ Neil, 2004 [32]
India	137.6	1.27	-	Kasim et al., 2002 [5]

4.2. Mortality Parameters

In the present study, the total mortality (Z) of S. commerson in the coastal waters of the Sultanate of Oman was 0.63 yr^−1, which is the lowest value reported compared to all previous studies (Table 6). Al-Hosni and Siddeek [13] calculated seasonal rates of total mortality and found exploitation ratios indicating overfishing. Ben Meriem [33] suggests that this might not result from a general increase in F, but rather from changes in the exploitation pattern. Additionally, the catch of immature specimens (smaller fish) has increased in recent times compared to the 1980s [33]. Heavy exploitation of the juvenile fraction of the S. commerson population is emphasized by the sharp decrease in the number of survivors (only 18% of the recruit numbers reach L50), indicating a growth overfishing of the stock [33]. Since M is linked with longevity and the latter to the growth coefficient K, the M/K ratio is found to be constant among closely related species and sometimes within similar taxonomic groups [34]. The M/K ratio usually ranges between 1 and 2.5 [35]. In the present study, the M/K ratio for S. commerson was calculated at 2.

Table 6. Total, natural, and fishing mortality (Z, M, and F, respectively) of S. commerson reported from different countries.

Country/Region	Z	M	F	Source
Oman	0.63	0.18	0.45	Present study
Oman	1.32	0.44	0.87	Mcllwain et al., 2005 [21]
Oman	1.59	0.5	1.09	Jayabalan et al., 2011 [30]
Iran	1.93	0.54	1.39	Kaymaram et al., 2013 [7]
Iran	1.47	0.49	0.98	Shojaei et al., 2007 [31]
United Arab Emirates	0.88	0.26	0.62	Grandcourt et al., 2005 [23]
India	5.39	1.37	4.01	Kasim et al., 2002 [5]

4.3. Length at First Maturity

From Claereboudt [36], length at first maturity (Lm) of S. commerson is 74.38 cm for both sexes in the coast of Oman. The length at first capture (Lc50 = 74.38 cm) of S. commerson found in this study is close to the length at first capture (Lc50 = 66.5 cm) of S. commerson in Hormozgan’s study of the waters of Iran [11]. The L_C50 of S. commerson was lower than Lm50 (91.25 cm). Therefore, the stock status is experiencing growth overfishing in the coastal waters of Oman. In this case, a new catch size limit should be introduced, which should be higher than the size of Lm50 to protect the juveniles. Several studies have supported the higher economic value of larger S. commerson in terms of weight [37,38,39].

4.4. Yield per Recruitment

The optimal fishing mortality (F40%) was determined to be 0.15 yr⁻¹ for S. commerson. The current fishing mortality (F2019 = 0.45 ${\mathrm{y}\mathrm{r}}^{-1}$) is higher than F40%. Additionally, the reference points F0.1 (0.16) and Fmax (0.3) suggest that growth overfishing is unlikely to be occurring for this species. The F0.1 fishing mortality rate corresponds to a point on the yield-per-recruit curve where the slope is 10% of that at the origin, and with a management regime aimed at achieving a specific economic end [40]. The current fishing mortality of S. commerson is higher than F40% and F0.1. Therefore, the fishing pressure should be reduced to approximately 0.32 yr⁻¹, i.e., 29% from the present level of mortality, 0.45 yr⁻¹, to obtain a sustainable yield of S. commerson in Omani waters.

4.5. Length-Based Spawning Potential Ratio

The spawning potential ratio depended highly on the proportions of different maturity levels [21,22,41]. There is a lack of spawning potential ratio studies on S. commerson in both the Sea of Oman and the Arabian Sea. The current length-based spawning potential ratio (LBSPR) of S. commerson is 10%. The target reference point for sustainable fisheries is 40% LBSPR [42,43,44]. The spawning potential ratio depends highly on the proportion of different maturity levels [21,22,41]. The current SPR (10%) of S. commerson indicates recruitment overfishing in the investigated areas. The harvest strategy needs to reach 40% SPR for sustainable fishery management of S. commerson in Omani waters.

4.6. Length-Based Biomass (LBB)

The length-based Bayesian biomass (LBB) approach was employed to assess the biomass status of Scomberomorus commerson in Omani waters. This method is particularly well-suited for data-limited fisheries and has been widely applied to evaluate important fish stocks in various countries. The LBB model estimates the current stock biomass relative to the unfished biomass [5] and has been used extensively in global studies to determine the status of fish populations [45]. In this study, the LBB analysis suggested that a considerable portion of the catch consists of undersized individuals, while larger fish remain in the population, indicating a high proportion of juveniles in the stock. [46]. The B/B0 of the current study is 0.17, which is slightly less than the reference point. On the other hand, AlMusallami et al.’s [46] study indicates a higher B/B0 for the same species on the coast of the U.A.E. in the Arabian Gulf with 0.5. The findings revealed that Scomberoides commersonnianus is experiencing overexploitation along the Omani coastline, as evidenced by its current biomass, which accounts for only 17% of the unexploited (virgin) biomass (B/B0) and 44% of the biomass at maximum sustainable yield (B/Bmsy). These outcomes align with the stock assessments obtained from both the TropFishR and spawning potential ratio (SPR) models. Consequently, it is recommended that effective management strategies be introduced to help restore and enhance the biomass of S. commersonnianus populations in the Sea of Oman and the Arabian Sea.

According to McIlwain et al. [10] and Jayabalan et al. [2], kingfish (S. commerson) stock in the Sultanate of Oman waters was already considered overexploited over 15 years ago, which could explain the decrease in the S. commerson landings as well as the indications of growth overfishing and recruitment overfishing in the current study. Therefore, management strategies are highly needed for S. commerson fishery in Omani waters. The current length at first capture is 65 cm. In addition, management measures include a two-month closed season each year (15 August–15 October) to help rebuild the stock. Enlarging the capture size significantly increases the biomass and catch under the recruitment overfishing condition [30]. Therefore, there are some recommendations based on the results of this study:

• Increase the minimum legal size to >80 cm fork length.

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  Rationale: Lc₅₀ (65 cm) is lower than Lm₅₀ (91.25 cm), indicating that many fish are being caught before reaching sexual maturity. Increasing the minimum size would allow more individuals to reproduce, increasing yield per recruit to more than 2105.5 recruits per individual.

• Reduce current fishing mortality by at least 65%.

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  Rationale: Current fishing mortality (Fcurrent) exceeds the reference level needed to prevent recruitment overfishing. Reducing fishing pressure will help maintain sustainable stock levels and prevent further depletion.

• Implement a strong monitoring, control, and surveillance (MCS) system.

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  Rationale: Effective enforcement is required to ensure compliance with size limits and closed seasons, supporting the recovery of the stock and long-term sustainability of the fishery.

These measures, if implemented, are expected to increase biomass, improve recruitment, and enhance the economic value of kingfish while maintaining stock sustainability in Omani waters.

5. Conclusions

This study revealed a total overfishing condition of 42% for S. commerson in Omani waters. The fish were caught before reaching their maximum potential length and weight, indicating growth overfishing for S. commerson in the investigated areas. The current spawning potential ratio (SPR = 10%) is significantly below the reference point (SPR = 20%). Biomass was critically low (B/Bo = 0.17), and lower than the reference point of 0.20 (20%). Also, the current biomass is 44% of Bmsy (B/Bmsy = 0.44), which is significantly lower than the reference point of 1. The SPR, B/Bo, and Bmsy were lower than their respective reference point, indicating recruitment overfishing. Therefore, it is recommended that commercial catches should be the optimum length range between 117.9 cm and 144.1 cm to avoid growth overfishing. At the same time, a 29% reduction in fishing pressure might be necessary to control recruitment overfishing and prevent stock decline. Some fisheries management recommendations could be limiting the fishing effort based on the optimal fishing mortality and limiting the minimum legal size based on the optimal length at first capture. Considering the above, the S. commerson stock and spawning stock biomass could be increased, which would improve the economic value of kingfish and the livelihood of fishermen while maintaining stock sustainability.

However, it should be noted that the data used in this study were collected from a single year (2019). As such, the results reflect the stock condition for that period only and may not represent the current population status. Interannual variations in recruitment, environmental conditions, and fishing pressure could influence stock dynamics. Therefore, long-term, multi-year monitoring and additional assessments are necessary to confirm these findings and ensure effective management of S. commerson in Omani waters. Furthermore, more investigations might be conducted on operational management units, such as the ecosystem-based fisheries assessment approach (EBFA).