Stock status and spawning potential ratio of orange mud crab (Scylla olivacea, Herbst 1796) in the southwestern coastal waters of Bangladesh

Abstract

Scylla olivacea (Orange mud crab) is a second commercial invertebrate species exported from Bangladesh. Though a significant portion of exports are supported by aquaculture, their farming ultimately depends on their wild stocks. Unfortunately, unregulated exploitation has led to a significant decline in the natural biomass of this species, raising concerns about the sustainability of crab production in Bangladesh. The study aimed to assess the stock status of S. olivacea (Orange mud crab) from the Southwestern coastal water of Bangladesh. One-year length frequency (width frequency-WF for crustacean fishery) data were collected and analyzed using the LBB (Length-based Bayesian Biomass) and LB-SPR (Length-based spawning potential ratio) methods. The assessed width parameter depicted the exploitation of small-size individuals (W_c=< W_{c_opt}) of S. olivacea. The estimated B/B₀ (0.25) suggests that 75 % of the wild stock had already been harvested, and biomass cannot produce MSY. The mean estimates for SW_50 % and SW_95 % were 8.29 cm and 12.76 cm respectively, revealing the use of a small mesh-size net for crab harvesting. The assessed Spawning Potential Ratio (SPR) was 12 % which is below the SPR limit reference point (SRP) of 20 %. This research confirmed the overfished (F/M = 1.4) and overexploited (E = 0.58) status of S. olivacea in Bangladesh. To ensure the sustainability of coastal fisheries in Bangladesh, the authorities must take immediate management measures to control the overexploitation of this species.

Highlights

• •Scylla olivacea is overexploiting in the coastal water of Bangladesh.
• •The wild biomass of S. olivacea is not capable of producing a sustainable yield.
• •High fishing pressure causing overfishing of S. olivacea in Bangladesh.
• •S. olivacea needs immediate management measures for sustainability.

1. Introduction

The mud crab (Scylla spp.) has garnered increased global recognition as a premium seafood choice across numerous tropical and subtropical Asian nations [1]. There are four species of Scylla in Bangladesh: Scylla olivacea, S. serrata, S. paramamosain, S. tranquebarica, respectively [2]. However, S. serrata, one of the four known species, was once wrongly thought to be the most prevalent species in Bangladesh. Therefore, after a lengthy argument and scientific analysis of the Scylla genus, it is now verified as Scylla olivacea [3,4]. S. olivacea is a commonly known as the Orange Mud Crab and mostly available mud crab species captured in Sundarbans Mangrove and its nearby rivers in Bangladesh [3,5,6].

The orange mud crabs (Scylla olivacea) are the second most exported invertebrate after shrimp (Penaeus monodon) from Bangladesh [7]. S. olivacea are widely distributed throughout the Indo-West Pacific region, spanning from East and South Africa to Southeast and East Asia, as well as Northeast Australia, the Marianas, Fiji, and the Samoa Islands [6]. Its importance extends beyond economic contributions, as it plays a crucial role in the livelihoods of coastal communities, particularly in the southwestern regions of the country [1]. Consequently, they have emerged as commercially important aquaculture species. The farming and exploitation of this species have seen a dramatic rise since the late 1970s, driven by high global demand and its export potential in Bangladesh. However, due to a lack of effective crab hatcheries in Bangladesh and the strong demand for mud crabs on the world market, there has been a continuous increase in the harvest of S. olivacea from their wild stock [1]. It is now becoming apparent and very alarming that the capture of so many juvenile crabs can cause enormous pressure on the wild crab population [1]. Moreover, their sustainability has become a challenge due to climate change, habitat loss, and arbitrary exploitation, all of which pose detrimental consequences for ecosystems and societies. However, the sustainability of these practices is under threat due to the increasing pressures on wild populations, emphasizing the urgent need for effective management strategies to prevent overfishing and ensure the long-term viability of the species.

In fisheries management, stock assessment serves as a critical independent variable that influences our understanding of sustainable practices. Assessing the stock status involves evaluating key factors such as exploitation, biomass, leght of capture (Lc), maturity length (Lm), estimation of maximum and minimum catch size, and spawning potential ratio (SPR) which are all crucial for formulating sustainable management practices [8]. These assessments are essential to reduce the capture of juvenile and brood crabs and restore fishing mortality to a sustainable level. Thus, stock assessment play crucial role in developing effective management strategies that ensure the sustainability of the species, which is vital for maintaining healthy crab populations and supporting the economic stability of the communities that depend on crab fishery [9].

Several studies have been conducted on growth performance, recruitment, fattening, culture, marketing, economics, and taxonomic confirmation of mud crabs in Bangladesh [3,6,[10], [11], [12], [13], [14], [15]]. Additionally, a single piece of evidence on the population parameter of S. olivacea in the Shyamnagar Upazila at Satkhira District, adjacent to the Sundarbans Mangrove Forest in Bangladesh [1]. However, research on stock status of S. olivacea in the coastal waters of Bangladesh is limited, highlighting a significant research gap. This gap underscores the necessity of conducting the length-based stock assessment of S. olivacea in Bangladesh. The length-based stock assessment helps policy managers to reduce the capture of juvenile and brood crabs and restore fishing mortality to a sustainable level [8,9].

The novelty of this research lies in its application of advanced methodologies, such as the Length-based Bayesian Biomass (LBB) method [16] and Length-based Spawning Potential Ratio (LB-SPR) method [17]. The LBB and LB-SPR methods have not been widely applied in Bangladesh, making this study a pioneering effort in the sustainable management of mud crab fisheries. Both methods are suitable to assess the stock status of a data-poor fisheries and requires simple width-frequency (WF) data (Barman et al., 2022 [8]). The one year of WF data of S. olivacea were collected and analyzed from the southwestern coastal waters of Bangladesh. Thus, this research was aimed to evaluate the stock information of orange mud crabs (S. olivacea) in the coastal water of Bangladesh. The specific objectives of this research was to evaluate the stock status and spawning potential of S. olivacea from the southwestern coastal waters of Bangladesh to provide actionable recommendations for sustainable fisheries management.

2. Materials and methods

2.1. Sampling and data analysis

The study was conducted in Bangladesh's southwestern coastal area (Khulna division). A total of six (06) representative sampling stations or landing centers, namely, Paikgacha (22°35021.700N, 89°19030.300E) and Koyra (22°21008.000N, 89°17032.900E) "Fishery Ghat" from Khulna district, Mongla (22°29011.9900N, 89°35025.7900E) and Sarankhola "Fishery Ghat" (22°1204300N, 89°48030.400E) from Bagerhat district, Ashashuni "Hajrakhali Fishery Ghat" (22°25038.000N, 89°11038.800E) and Shyamnagar "Fishery Ghat" (22°14054.0600N, 89°14017.4500E) from Satkhira district were selected for WF data collection, respectively (Fig. 1). The study was carried out over twelve (12) months, from January to December 2022, and width-frequency (WF) data were collected monthly.

Fig. 1.

The figure showing the location and sampling sites of the study area.

The distance between the points of the posterior-most lateral spines is used to define carapace width as the standard measurement, followed by Kampouris et al. [18]. The onboard WF data were collected directly from commercial and artisanal fishing vessels and the local landing centre, "Fishery Ghat." Crab harvesting in the southwestern waters is a common activity involving hooks baited with small fish to lure crabs. Experienced fishermen also use baited basket traps in shallow waters to capture crabs. This method has been used for generations and remains popular to catch crabs in this region. In this project, we collected samples from the baited basket traps and hooks too. A maximum representation of all width and age class samples was collected during sampling to avoid analytical error. During the adverse weather conditions, in some cases, samples were collected and preserved in the icebox and immediately transferred to the Aquatic Ecology laboratory under the Department of Fishery Resources Conservation and Management at Khulna Agricultural University, Khulna. A total of 1777 individuals of crabs were sampled and measured for this research. The WF data were measured using digital slide calipers and recorded in unit millimeters (mm). Based on 1 cm (10 mm) class intervals (CI), the obtained samples were categorized for further analysis. The R-code (LBB 33 a.R) was used to evaluate the WF data of S. olivacea from Bangladesh's Southwest Coastal Water (Table 1), which were accessed on July 10, 2021 and downloaded from the link- http://oceanrep.geomar.de/44832/

Table 1.

The input parameters and prior information for S. olivacea.

Min W (mm)	15	Prior Winf (mm)	163
Max W (mm)	154	Prior Z/K	3.3
Class intervals (mm)	10	Prior M/K	1.5
Total individuals	1777	Prior F/K	1.77
Prior $\left(\alpha \right)$ alpha	9.8	Prior Wc (mm)	6.53

2.2. General description of the length-based Bayesian Biomass (LBB) method

Using width-frequency (WF) or Length-frequency (LF) data, the LBB offers a novel technique for estimating a data-poor fishery's size structure and stock status. It involves the simultaneous study of all pertinent parameters using the Bayesian MCMC (Monte Carlo Markove Chain) method [16]. LBB is a newly developed and robust method for evaluating the WF data of commercially exploited invertebrates. This method requires only WF data of invertebrate species that grow throughout their life. It is thought that von Bertalanffy's law [19] growth equation (Equation (1)), in the form provided by Beverton and Holt [20], governs the increase in width or length of species, i.e.:

$$W_t=W_{inf}\left[1-e^{-k\left(t-t_0\right)}\right]$$ (1)

In this equation, W_t stands for the width at t age, W_inf for asymptotic length, the rate at which W_inf is approached denoted by K, and t₀ for hypothetical age at zero length. When the gear is thoroughly selected for the crabs, total mortality (Z=M + F) relative to K determines the catch's curve in the number-at-width curve. equation (2) expresses this curve:

$$N_W=N_{W_{start}}{\left(\frac{W_{\mathit{inf}}-W}{W_{\mathit{inf}}-W_{start}}\right)}^{Z/K}$$ (2)

Where the number of survivors with width W stands for N_w, the number at length W_start over the entire selection stands for N_Wstart, from which the gear draws all individuals entering it, and Z/K for the ratio of overall mortality to the somatic natural growth rate [16], when M/K equals Z/K, W_start = 0, N_Wstart = 1 for the unfished state. Thus, equation (2) is simplified as following (Equation (3)):

$$\frac{P_W}{W_{\mathit{inf}}}={\left(1-\frac{W}{W_{\mathit{inf}}}\right)}^{M/K}$$ (3)

The P_W/W_inf denotes the likelihood of surviving to the length of W/W_inf, which depends on the M/K ratio [16]. The width vulnerable to partial selection is influenced by fishing gears, as explained by equation (4):

$$S_W=\frac{1}{\left[1+e^{-\alpha \left(W-W_c\right)}\right]}$$ (4)

In this equation, α indicates the steepness of the ogive, and S_W means the specific proportion that the gear occupies at width W [21,22]. The width length is equivalent to the gear mesh size, keeping a possibility, and P is obtained by equation (5).

$$W_P=\frac{{\alpha W}_C-\log \left(\frac{1}{p}-1\right)}{\alpha }$$ (5)

In this case, W_C and α are specified above, and W_P represents the width with the probability P that it will be taken by the gear [16]. The ogive selection parameters can be evaluated by fitting the following equation (Equation (6)), along with W_c, W_inf, F/K, and M/K.

$$N_{W_i}=N_{W_{i-1}}{\left(\frac{W_{\mathit{inf}}-W_i}{W_{\mathit{inf}}-W_{i-1}}\right)}^{\frac{M}{K}+\frac{F}{K}{S}_{W_i}}$$ (6)

And

$$C_{W_i}=N_{W_i}{S}_{W_i}$$ (7)

In these two equations, W_i denotes individual numbers at i the width, W_i-1 denotes the prior width number, and C is for unique numbers sensitive to gear damages [16]. By dividing the two sides of Equation (7) by the corresponding sum, equation (8) describes the normalization and comparison of different year samples.

$$\frac{C_{W_i}}{\sum C_{W_i}}=\frac{N_{W_i}{S}_{W_i}}{\sum N_{W_i}{S}_{W_i}}$$ (8)

Adjusting equation (8) to WF data, F/K and M/K estimations are generated. These estimates can combine to obtain F/M=(F/K)/(M/K) or vice versa. To complement the LBB equation, the JAGS (a Bayesian Gibbs sampler program) and the R statistics were used to fit the observed proportionate length P_wi with its projected P^{^}_Li value. Equation (9) launched the width distribution P^{^}_Wi based on the equation and expressed as-.

$${\widehat{P}}_{W_i}=\frac{{\widehat{N}}_{W_i}}{{\sum \widehat{N}}_{W_i}}$$ (9)

Finally, the process for approximating stock status from W_inf, F/K, M/K, and W_C are summarized in equations (10), (11)) [23]. However, the maximal biomass of a cohort can be evaluated by equation (10) after first accounting for the estimation of W_inf, W_opt, and M/K.

$$W_{opt}=W_{\mathit{inf}}\left(\frac{3}{3+\frac{M}{K}}\right)$$ (10)

Based on the outcomes of Equation (10) and the F/M (current fishing pressure), Equation (11) might be used to calculate the maximum catch, mean width at initial capture, and optimum width of initial capture (W_{c_opt}):

$$W_{c_{opt}}=\frac{W_{\mathit{inf}}\left(2+3\frac{F}{M}\right)}{\left(1+\frac{F}{M}\right)\left(3+\frac{M}{K}\right)}$$ (11)

The Z/K and M/K are equal for an unfished fishery where the value of N_Wstart is zero (0), and the value for W_start is one (1). Further, to produce maximum sustainable yield (MSY), W_{c_opt} was used [16]. The overfished situation is indicated by F/M>1, and the underfished condition by F/M<1. The LBB approach was used to evaluate and convert the B/B_MSY and the relative size of the stock, or exploited biomass, compared to unexploited biomass (B/B₀), to assess the stock status. The stock was categorized based on the B/B_MSY values and explained as B/B_MSY>1.1 is healthy stock, 0.8<B/B_MSY ≤1.1 is slightly overfished, 0.5<B/B_MSY ≤0.8 is overfished, 0.2<B/B_MSY ≤0.5 is grossly overfished, and B/B_MSY <0.2 is collapsed. However, the reference limit for the B/B₀ ranged from 0.4 to 0.5 [16].

The proportions of W_mean/W_opt and W_c/W_{c_opt} are less than the unity (0.9), indicating the capture of small individuals, and the fishery's length structure is truncated. Again, the value of W_95th/W_inf close to unity (0.9) signifies the minimum number of large individuals. The B/B₀ < B_MSY/B₀ recommended the reduction of fishing pressure or catch, while W_c < W_{c_opt} recommended that the size of the fish caught must be bigger than the observed catch size [16,24].

The LBB method findings on relative biomass and W_c are thus helpful in managing fisheries with little data. The priors of W_inf, W_c, M/K, F/K, Z/K, and α) for the LBB analysis are shown in Table 1. The parameters of the LBB method are crucial for determining how to fish sustainably for marine resources.

2.3. Length-based spawning potential ratio (LB-SPR)

Spawning potential ratio (SPR) is a widely used fisheries reference point that has strong theoretical background for fisheries management. The length-based spawning potential ratio (LB-SPR) method is a testified approach to estimating the SPR of aquatic organisms particularly when M/K > 0.53 [[25], [26], [27], [28]]. Unlike any other equilibrium stock assessment model, the LB-SPR works based on several assumptions, such as asymptotic selectivity, the von-Bertalanffy equation accurately describes the population growth, length at age is normally distributed, the natural mortality rate remains constant throughout the adult age group, and constant growth rate throughout the cohort of the stock [29].

LB-SPR method needs only width frequency (WF) data for shellfish or length frequency (LF) data for fish [17]. The LB-SPR method also requires W_∞, M/K, width at 50 % maturity (W₅₀) and width at 95 % maturity (W₉₅) of the population as input parameters [29]. In this research, the LBB-derived W_∞ and M/K values were used as input parameters for the LB-SPR analysis. Additionally, equation (12) [30] and equation (13) [29] were applied to calculate the W₅₀ and W₉₅ which serve as the input for the LB-SPR method (Table 2).

logW₅₀ = 08979logW_∞- 0.0782 (12)

W₉₅ = 1.1 × W₅₀ (13)

Table 2.

Input parameters for the LB-SPR method for S. olivacea from Bangladesh.

Parameter	Values
W∞	16.50 cm
M/K	1.33 year−1
Length at 50 % maturity (W50)	10.35 cm
Length at 95 % maturity (W95)	11.37 cm

The LB-SPR uses the maximum likelihood method to estimate the width of the first capture of 50 % population (SW_50 %) and the width of the first capture of 95 % population (SW_95 %). Additionally, the LB-SPR method estimates the relative fishing mortality (F/M) which is further used to calculate the SPR value [17,29]. The LB-SPR analysis was conducted using an R-code (LB-SPR package) downloaded from the following link https://cran.r-project.org/web/packages/LBSPR/index.html (access date: 30 March 2022) and the target SPR was set as SPR = 40 %.

3. Results

3.1. State of S. olivacea in the coastal water of Bangladesh

The research sampled 1777 individuals of S. olivacea samples from the coastal water of Bangladesh during the study period. Fig. 2 present the distribution of carapace width frequency (WF), classified into 10 mm size intervals. The minimum width was 15 mm, while the maximum width was recorded at 154 mm. Among them, 37 % were juveniles, and their carapace width was up to 74 mm. Most individuals were collected during sub-adult stages with 75–124 mm carapace widths. Only 3 % of specimens were adults with a carapace width above 124 mm. The analysis of the collected crab samples revealed an interesting sex ratio distribution. Specifically, out of all the samples collected, 41 % were female and 59 % were male. The correlation figure (Fig. 3) showe female appear highly correlated compare with male samples for S. olivacea. However, during the adult stage, the male population was observed to be more dominant, accounting for 72 % of the sampled crabs. This contrasts with the female population, which only comprised 28 % of the adult samples.

Fig. 2.

Size class distribution of collected male and female S. olivacea in the Southwestern coastal waters of Bangladesh.

Fig. 3.

Correlation figure showe female appear highly correlated for S. olivacea in the Southwestern coastal waters of Bangladesh.

3.2. Stock status of S. olivacea

The population parameters and stock status of S. olivacea were evaluated by the LBB method and tabulated in Table 3. The computed B/B_MSY was 0.67, indicating the overfishing state of the S. olivacea stock because the biomass cannot produce MSY at the same rate. The calculated B/B₀ (0.25) was below the reference limit, indicating the overfished condition because their wild stock had been reduced by 75 %. Furthermore, the calculated B/B₀ (0.25) was smaller than the B_MSY/B₀ (0.37), supporting that the wild S. olivacea stock is being overharvested. A condition of overfishing of this wild population was also indicated by the estimated F/M (1.4) and F/K (1.9), which were higher than the optimum (1.0). Additionally, the estimated exploitation rate (E = 0.58) was higher than the permitted maximum rate of exploitation (E = 0.50), and the valued Z/K (3.3) was higher than unity, both of which suggested overexploitation and overharvesting of the S. olivacea in Bangladesh. Therefore, the findings of this present study pointed to the alarming state of this natural population, which would soon be a critically endangered species.

Table 3.

Estimated LBB results of S. olivacea using WF data.

Width parameters		Different width ratios		Stock information
Wmean(cm)	10.7	Wc_opt/Linf	0.60	M/K	1.33 (1.05–1.61)
Winf(cm)	16.5	Wopt/Winf	0.69	F/M	1.44 (1.03–2.22)
Wopt(cm)	11.0	Wc/Winf	0.51	F/K	1.94 (1.56–2.46)
Wc_opt(cm)	9.9	Wmean/Wopt	0.93	Z/K	3.29 (2.98–3.63)
Wc50(cm)	8.46	Wc/Wc_opt	0.86	B/B0	0.25 (0.15–0.41)
Wc95(cm)	13.1	W95th/Winf	0.93	B/BMSY	0.67 (0.4–1.1)
W95th(cm)	15.4	E	0.58	BMSY/B0	0.37
Stock Status	Overfished and overexploitation of S. olivacea in Bangladesh

Even though the calculated W_mean/W_opt (0.93) was somewhat greater than unity (0.9), the estimated W_c/W_{c_opt} (0.86) was lower than the limit. The condition of having a distinct length structure also pointed to the overfishing of this wild population. However, there were enough substantial larger S. olivacea species present, as indicated by the valued W_95th/W_inf (0.93) being higher than the unity (0.9). However, the calculated W_c (8.51 cm) was lower than W_{c_opt} (9.9), intending to catch of smaller crabs on the first try. As a result the decreasing numbers imply problem where growouts could not have sufficient mature time before being captured. Therefore, B/B₀<B/B_MSY and W_c < W_{c_opt} directed that lowering fishing pressure and catching of large-size crabs may be advantageous for S. olivacea wild populations of the coastal areas, particularly in the Sundarbans area of Southwest Bangladesh (Fig. 4).

Fig. 4.

LBB-derived results for S. olivacea in the Southwest coastal waters of Bangladesh.

3.3. Life history ratio, maturity size, and spawning potential of S. olivacea

The input parameters for LB-SPR analysis are given Table 2. The anticipated growth curve of the LB-SPR method was well-fitted and skewed towards the small size width class for collected width frequency data of S. olivacea from Bangladesh (Fig. 5A). The selectivity and maturity of the ogive curve indicated that the width of maturity is higher than the width of the first capture (Fig. 5B). The mean estimates for the 50 % selectivity (SW_50 %) and 95 % selectivity (SW_95 %) stand at 8.29 cm and 12.76 cm, respectively, signifying the use of a small mesh-size net for crab harvesting in the coastal region of Bangladesh (5C). The mean estimate of F/M was 2.45 which is two times higher than the threshold limit (F/M = 1.0) (Fig. 5C). The assessed spawning potential ratio (SPR) from the LB-SPR method was 0.12 which is below the SPR limit reference point (LRP) of 20 % (Fig. 5C). Fig. 5D displayed the width for the crab necessary to achieve the threshold target SPR limit (SPR = 0.40), highlighted in red color. However, the current width class for crabs is smaller than the expected width class size, suggesting the predominant harvesting of juvenile crabs in the coastal region of Bangladesh.

Fig. 5.

LB-SPR derived figures for S. olivacea in the Southwest coastal waters of Bangladesh show: (A) the bar diagram indicates the observed width frequency (WF) of collected crab samples and the solid black curve line indicates the LB-SPR model fitted predicted size distribution of crab samples. (B) maturity viz selectivity curve from the fitted LB-SPR model where W_50 %=10.35 cm and W_95 %= 11.37 cm. (C) The distribution of the 50 % selectivity (SW_50 %=8.29) and 95 % selectivity (SW_95 %= 12.76 cm), relative fishing mortality (F/M = 2.45) and spawning potential ratio (SPR = 0.12). (D) observed viz expected size composition data at SPR target level 0.4 (SPR = 40 %).

4. Discussion

4.1. Suitability of application of LBB and LB-SPR methods

S. olivacea seeds were predominantly collected from the coastal waters of Bangladesh for crab farming. Additionally, these crabs were unintentionally caught by artisanal and commercial fishing as bycatch. Despite being harvested for several decades, there are no catch records for these species. Detailed fishery information is unavailable except for the length-frequency (WF data for crustaceans) data for S. olivacea, the so-called data-poor fisheries. Complete stock assessments often require data sets beyond fisheries, making them unsuitable for data-limited scenarios. In the absence of independent fisheries data, it is difficult to assess the stock status of data-poor fisheries [16,24,31,32]. In this case, LBB and LB-SPR can serve as an appropriate stock evaluation approach.

LBB and LB-SPR are the two most powerful techniques for the stock analysis of data-poor crustaceans or fishes [16,17]. Each method requires only length frequency (LF) data for fish and width frequency (WF) data for crustacean or shellfish organisms. The primary assumption for the LBB technique was that the LF or WF data could represent all-size individuals in a stock [16]. Both methods are highly sensitive to input parameters and the output from LBB can be used as input for the LB-SPR analysis and other stock assessment methodologies [16]. Both methods provide critical management information for exploited fishery management. Moreover, compared to other classical methods (such as Surplus Production Models and Beverton-Holt Y/R analysis), the LBB and LB-SPR signify a more valid approach [8,[33], [34], [35]].

However, the validity of the LBB and LB-SPR approach largely depends on the unbiased representation of the WF data [16,17,36]. This research carefully took all the width group data during sampling; thus, this study ensured the representation of every size group of S. olivacea from the study area. Thus, the application of LBB and LB-SPR were the most suited approaches only using the WF data from all potential length classes for the S. olivacea in Bangladesh.

4.2. Population characteristics, stock status, and SPR of S. olivacea

In the current study, carapace-width (CW) frequency data from various size classes of S. olivacea orange mud crab were utilized to estimate the wild population of these species over the Southwest coastal waters of Bangladesh using the LBB method. The size frequency distribution of a species determines which particular catch group-for instance, juveniles, sub-adults, and adults-is more vulnerable to fishing pressure or gear [1]. In this study, the highest CW for S. olivacea was obtained at 154 mm, compared to 148 mm in India [37] and 134 mm in Malaysia [38].

Most of the individuals that were collected were juveniles or subadults. This is because the coastal community usually harvests small crabs as seeds for further farming of mud crabs in Bangladesh. These findings are also consistent with various studies that have been conducted in the coastal regions, particularly in the areas near the Sundarbans [1]. To prevent skewed LBB results, we collected possible small and large samples from the landing centers in the Southwest coastal waters of Bangladesh.

The maximum yield can be obtained when the length at first capture (W_c) is very close to the value of the optimum length of capture (W_opt) and the growth overfishing can be avoided when W_c is equal or larger to the optimal length of first capture (W_{c_opt}) [16]. A different length structure and the capture of relatively young individuals of S. olivacea were revealed by the LBB results (W_mean/W_opt = 0.93 and W_c/W_{c_opt} = 0.86). However, in addition, the estimated W_c (8.51) and W_{c_opt} (9.9) indicated the harvesting of small-size crabs. The LB-SPR-derived SW_50 % (8.29 cm) and SW_95 % (12.76 cm) indicated the current width class for crabs is smaller than the expected width class size, depicted the use of a small mesh-size net and predominant harvesting of juvenile S. olivacea in the coastal region of Bangladesh. The findings of Rouf et al. [1] and Sakib et al. [5] also testified to the harvesting of young and small-sized crabs from the natural waterbodies in Bangladesh. Nowadays, the demand for crab is increasing in national and international markets. Thus, crab farming becoming a promising economic activity in the southwestern coastal region of Bangladesh [2]. However, there is a lack of crab hatchery facilities in Bangladesh, so the coastal community completely depends on nature for crab fry and collects young crabs as seedlings for their farm using fine mesh nets [6].

This study estimated higher fishing mortality than the optimum (LBB-derived F/M = 1.4 and F/K = 1.9, and LB-SPR derived F/M = 2.45), indicating a non-equilibrium stock condition of S. olivacea in the coastal water of Bangladesh. According to Gulland [39], the yield is optimum when the fishing mortality is equal to the natural mortality (F=M). In this research, the estimation of exploitation was higher than the optimum (E = 0.58) indicating the overexploitation condition of S. olivacea. Ideally, the value of E is 0.50, revealing the optimum status of an aquatic species, and thus when exploitation is greater than 0.50 (E > 0.50), it specifies the overfishing condition of the aquatic species [39]. Thus, this research depicted that the high fishing pressure and overexploitation may lead to the S. olivacea population collapse. Similar findings are also reported by Sakib et al. [5], Viswanathan et al. [40], and Hamid et al. [41] for different crab populations in this study region.

The LB-SPR approach showed robustness in estimating the SPR value, particularly for the aquatic species with M/K > 0.53 and uni/bimodal length or width distribution data [17]. The SPR from the LB-SPR method was 12 % (SPR = 0.12) which is below the SPR limit reference point (SRP) of 20 %. The SPR is a well-established biological reference point to assess the impact of current fishing pressure on the reproductive potential of a selected stock [8,17,29]. A low SPR value is produced when there are very few large and mature individuals present in the natural stock and a high frequency of small and immature individuals is observed in the catch composition [17]. The estimated SPR value of this study indicated the growth and recruitment overfishing of S. olivacea.

4.3. Strength, limitations, and future research

The meticulous handling of the one-year WF data and the utilization of two comprehensive methodologies (LBB and LB-SPR) ensure the scientific and statistical integrity of this research, along with its ethical robustness. However, it is important to note that the samples were obtained from the landing sites within the specified study area, which could potentially lead to misinterpretations regarding the precise geographical locations of the samples, and the findings and management recommendations of this research should not be generalized to encompass the entire coastal waters of Bangladesh. Although a year's worth of data is sufficient for conducting LBB and LB-SPR analyses, it's crucial to acknowledge that population parameters may fluctuate from one year to the next year. Thus, this research provides the baseline management information and continuous stock assessment of S. olivacea in Bangladesh is needed for their sustainability. Additionally, further research focusing on the biology, breeding, and hatchery management of S. olivacea is imperative to ensure their long-term sustainability.

5. Conclusion and recommendations

The orange mud crab (S. olivacea) is one of the major commercial fishery in in coastal area of Bangladesh. S. olivacea experiencing 40 % overfishing (F/M = 1.4) and overexploitation (E = 0.58) in the southwestern coastal water of Bangladesh. Additionally, the reproductive potential of this species is also alarmingly low (SPR = 0.12). Therefore, it is urgent to adopt proper management practices. This research suggests the following recommendations to protect the wild population of S. olivacea in Bangladesh:

• a)The capture of S. olivacea must be kept above 9.9 cm in size.
• b)Immediately reduce fishing mortality by controlling fishing efforts.
• c)Take effective actions to stop the harvesting of juvenile crab for aquaculture.
• d)Establish hatcheries for quality crab fry production to expand and support the promising carb aquaculture industry.

The results of this study underscore the importance of implementing comprehensive management strategies for S. olivacea in Bangladesh, aimed at preserving a balanced coastal ecosystem. Additionally, gaining insights into the status of the wild S. olivacea stock will enable researchers to make informed decisions regarding management and sustainability, thus fostering socioeconomic development and the sustainable utilization of Bangladesh's coastal and marine resources.

CRediT authorship contribution statement

Sanzib Kumar Barman: Writing – original draft, Resources, Investigation, Funding acquisition, Data curation. Md Jahid Hossain: Writing – review & editing, Visualization, Investigation, Data curation. Md Ashiqur Rahman Shesir: Writing – review & editing, Visualization, Investigation, Data curation. Sabbir Hossain: Writing – review & editing, Visualization, Data curation. Partho Protim Barman: Writing – review & editing, Writing – original draft, Validation, Supervision, Software, Methodology, Formal analysis, Conceptualization.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Sanzib Kumar Barman reports financial support was provided by Research and Development Project (R&D), Ministry of Science and Technology, Bangladesh. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following is the Supplementary data to this article: