ORIGINAL RESEARCH article

Front. Mar. Sci., 27 August 2021

Sec. Marine Fisheries, Aquaculture and Living Resources

Volume 8 - 2021 | https://doi.org/10.3389/fmars.2021.731837

Stock Assessment of 19 Perciformes in the Beibu Gulf, China, Using a Length-Based Bayesian Biomass Method

  • 1. College of Fisheries, Guangdong Ocean University, Zhanjiang, China

  • 2. CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China

  • 3. Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China

  • 4. Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China

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Abstract

The Beibu Gulf in China is rich in fish resources. However, only a small number of commercially developed fish stocks have been specifically assessed owing to limited data and expertise. In this study, 19 perciform fish populations in the Beibu Gulf were assessed using a length-based Bayesian biomass (LBB) estimator method, which is a new approach to evaluate a fishery’s status using length frequency (LF) data. The results showed that only 21% of the evaluated stocks were healthy and 79% were overfished. In particular, 26 and 21% of the assessed species had collapsed and were grossly overfished, respectively. Only 11 and 21% of the assessed species were slightly overfished and overfished, respectively. The ratios between the mean and optimum length (Lmean/Lopt) and between the mean length at first capture and the mean length, which maximizes catch and biomass (Lc/Lc_opt), were below one in 14 out of the 19 stocks, suggesting a truncated length structure and fishing of undersized individuals. The ratio of the 95th percentile length to asymptotic length L95th/Linf was close to one (>0.9) in 10 of 19 stocks, suggesting that at least some large fish were still present. Our research confirmed that the fishery resources in the Beibu Gulf were seriously overfished and provided evidence that LBB was an efficient method to evaluate the fishery resources. Fishery managers need to take specific measures to restore fishery resources.

Introduction

World fisheries, including freshwater, marine, and capture fisheries, as well as aquaculture, provide approximately 17% of the total animal protein consumed by humans, and around 56.6 million people are directly engaged in fisheries (Kang et al., 2018). After decades of rapid development, China has become the largest contributor to global marine fishing (FAO, 2019). At present, China’s marine catch exceeds 15 million tons (Wang Y. et al., 2020). However, since the 1970s, many of China’s marine fishery resources have been over exploited and the structure of the fish community has greatly changed (Kang et al., 2018; Zhang et al., 2020); the catches of some traditionally important economic fish have decreased significantly (Jin et al., 2015; Zhang et al., 2020). Only approximately 12% of the global fisheries are properly managed through stock assessments results (Kindong et al., 2020). Therefore, stock assessment is essential for the management of fisheries resources.

The South China Sea is located at the center of the Indo Western Pacific region and is the third largest marginal sea in the world (Li et al., 2019). It is rich in marine biodiversity, with more than 8,600 species of animals and plants (Ng and Tan, 2000). Perciformes play an important role in the structure of fish resources in the South China Sea, which have complex feeding habits, feeding on phytoplankton and zooplankton as well as other Marine animals such as invertebrates and fish. There are 979 species of Perciformes in the whole South China Sea, accounting for 42.2% of the total species (2321) (Ma et al., 2006). There are more than 300 species of Perciformes in the Beibu Gulf in the South China Sea, accounting for more than 50% of the total fish species, and most of them are economically important fish (Sun et al., 2010).

In China, only a small number of commercially developed fish resources have been specifically assessed, owing to limited data and expertise (Liang et al., 2020). Recently, two methods have been applied to the assessment of fishery resources in China. One is the maximum sustainable yield (MSY) model, which uses a time series of catch and auxiliary data to estimate the MSY (Ju et al., 2020b; Liang et al., 2020; Zhai et al., 2020); The other is the length-based Bayesian biomass (LBB) model, which uses length frequency (LF) data to estimate asymptotic length, length at first capture, relative natural mortality and relative fishing mortality (Ju et al., 2020a; Kindong et al., 2020; Liang et al., 2020; Wang Y. et al., 2020, 2021; Zhang et al., 2020, 2021; Wang X. et al., 2021). Size measurement is the basic requirement for marine fishery resource surveys in China (Jin et al., 2012), and LF data are usually easier to obtain and cheaper than other data types (Liang et al., 2020). This allows the LBB method to be used to evaluate the commercial fishery resources in China’s marine waters where there is little knowledge of other parameters (Zhang et al., 2020). LBB is a newly developed Bayesian biomass estimation method based on length, which needs no data except LF (Froese et al., 2018). The growth and mortality parameters and the relative stock size are estimated using a Bayesian Monte Carlo Markov chain (MCMC). Furthermore, LBB results can be informative for other data poor stock assessment models that use priors for the status of the biomass [e.g., AMSY or Catch-MSY (CMSY)], regarding the relative biomass (B/B0) in a certain year.

In this study, we applied the LBB method to 19 Perciform fish populations in the Beibu Gulf to explore the extent of biomass depletion caused by fisheries, and to provide evidence for potential alternative harvest policies.

Materials and Methods

Data Sources

The data were collected by four surveys with single bottom trawls of “Beiyu 60011” from 2010 to 2011, which had the same selectivity as when fishing commercially. The main engine power of the survey vessel was 514.5 kW, the mouth of the bottom towing net was 42 × 7 m, and the mesh size (inner diameter) was 40 mm. At each station, a trawl was towed for 2 h at a speed of 3 kn. The survey area was in the northern part of the South China Sea (20.75° N–21.25° N, 112.75° E–114.25° E) and 18 survey stations were established (Figure 1). Samples were identified to species level in the laboratory, and their standard body length was measured. The scientific names of the species in this study were verified from the FishBase,1 as summarized in Table 1. The specific LF data is shown in Supplementary Material 1.

FIGURE 1

FIGURE 1

Location of the 18 stations (bold dots) with the bottom trawl in the South China Sea.

TABLE 1

Scientific name Min (mm) Max (mm) Class interval Number L inf (cm) Z/K prior M/K prior F/K prior Lc prior Alpha prior
Acropoma japonicum 27 91 3 162 11 2.2 1.5 0.661 5.05 25.4
Pennahia microcephalus 59 236 5 333 29.4 3 1.5 1.47 8.67 57.2
Ariomma indica 78 152 5 186 17 3.9 1.5 2.44 9.69 29.5
Branchiostegus argentatus 76 298 5 263 30.2 9 1.5 7.53 9.69 65.8
Decapterus maruadsi 71 292 5 772 33.3 1.6 1.5 0.118 10.7 32.4
Parastromateus niger 94 268 5 111 28.6 8.4 1.5 6.92 11.7 35.4
Johnius belangerii 75 170 5 553 17.2 1.1 1.5 0.3 9.95 36.1
Nemipterus japonicus 64 209 5 828 21.2 4.4 1.5 2.93 9.69 21.4
Nemipterus peronii 65 150 5 240 15 2 1.5 0.498 7.96 20.6
Nemipterus virgatus 62 286 5 669 30.8 7.2 1.5 5.72 10.7 17.9
Evynnis cardinalis 41 196 10 1309 20 4 1.5 2.51 8.16 15.2
Pennahia anea 72 166 5 168 20.1 1 1.5 0.3 11 22.1
Pennahia pawak 65 203 5 1845 20.7 2.3 1.5 0.789 8.67 42.2
Siganus fuscescens 82 201 5 117 24.3 3.5 1.5 2.04 12.2 44.9
Terapon theraps 60 206 5 1083 20.7 6.7 1.5 5.22 9.44 23
Trachurus japonicus 65 188 5 809 20 1.8 1.5 0.295 11 20.4
Trichiurus japonicus 65 257 5 168 30.3 8.6 1.5 7.1 11.2 80.6
Upeneus bensasi 77 145 5 143 14.7 2.8 1.5 1.32 9.95 45.7
Upeneus moluccensis 60 184 5 370 18.8 4.9 1.5 3.41 8.93 23.7

Basic information and priors of 19 species used in this present study.

In this study, all analyses were performed using the R-code (LBB_28. R), which can be downloaded from http://oceanrep.geomar.de/44832/ along with a New User Guide.

Declaration Statement

Our manuscript was based on survey cruise data and no live vertebrates or higher invertebrates were involved; therefore, we believe an ethical review process was not required for our study.

General Description of the LBB Method

The LBB estimator is a new method to analyze the LF data of economic fishery catches (Liang et al., 2020). The LBB model is suitable for species that grow throughout their lives, such as most economic fish and invertebrates, and only LF data is needed to evaluate them (Froese et al., 2018). It estimates asymptotic body length (Linf), first catch body length (Lc), relative natural mortality (M/K) and relative fishing mortality (F/M) in the age range represented by LF samples. These parameters were used as inputs to estimate the ratio (B/B0) of the depletion or currently developed biomass to the undeveloped biomass using the standard fishery equation (von Bertalanffy, 1938; Beverton and Holt, 1957).

These parameters can be used to estimate the Lc of the maximum catch and the ratio of MSY to undeveloped biomass (BMSY/B0). Froese et al. (2018) considered that no significant difference is found between the estimated relative biomass of LBB and the “true value” in all cases assessed in their study, and the value in the simulation data is similar to the independent estimated value of the complete inventory assessment. The median maximum body length of the validation year is used as the prior value of Linf instead of the default absolute maximum body length (Froese et al., 2018; see also Froese et al., 2019).

The LBB method first estimates the asymptotic body length Linf, the first catch body length Lc, the average M/K and the F/K in the past few years, provided that 50% of the individuals are caught by fishing gear. If the value of Linf can be obtained from independent studies, it can be introduced as a prior value to reduce the uncertainty of LBB evaluation. With these parameters, the relative size of the current population can be calculated from the standard fishery equation.

In this study, we only show the basic equations below. The detailed methods can be found in Froese et al. (2018).

First, it is assumed that the growth in length follows von Bertalanffy’s (1938) growth equation, in the form assigned by Beverton and Holt (1957):

where Lt is the length at age t, Linf is the asymptotic length, K is the rate at which Linf is approached, and t0 is the theoretical age at zero length (Liang et al., 2020).

If the fishing gear is completely selective, the catch on the body length curve is a function of the total mortality related to K. The equation of this curve is as follows:

where NL is the number of survivors to length L, NLstart is the number at length Lstart with full selection; that is, from which all individuals entering the gear are retained by the gear, and Z/K is the ratio of the total mortality rate Z to somatic growth rate.

In addition to the parameters in Equation 2, the catch affected by partial selection is the selectivity function of fishing gear (assumed to be trawl type) of each species given by the function in Equation 3:

where SL is the fraction of individuals that are retained by the gear at length L, and α describes the steepness of the ogive (Froese et al., 2018).

To estimate Linf, Lc, α, M/K and F/K simultaneously, Equation 2 must be replaced by a difference equation fitting the whole fishing quantity curve:

and

where Li is the number of individuals at length i, Li–1 is the number at the previous length, where C refers to the number of individuals vulnerable to the gear and all other parameters are as described above (Froese et al., 2018).

Finally, according to the estimated values of Linf and M/K, the Lopt with the maximum biomass of the undeveloped population is obtained from Equation 6:

On the basis of a given fishing pressure (F/M) and Equation 6, the mean length at first capture, which maximizes catch and biomass (Lc_opt), can be obtained from:

Estimates of Lc_opt are used below to calculate a proxy for the relative biomass that can produce the MSY (Froese et al., 2018).

Parameter F/M > 1 indicates that the assessed stocks are being overfished, and parameter B/B0 < 1 indicates that the current biomass is lower than that unfished biomass. In particular, B/B0 < 0.5 indicates that the existing biomass of the stocks is already at a very low level. If the ratios (Lmean/Lopt and Lc/Lc_opt) are below 1 indicate a truncated length structure and fishing mortality concentrated on small individuals. If the parameter of the 95th percentile length to asymptotic length L95th/Linf is close to one (>0.9), this suggests that there are at least some large fish in this region. The stock status was evaluated according to the estimated value of B/BMSY, showed in Table 2 (Froese et al., 2018; Palomares et al., 2018; Ju et al., 2020a; Liang et al., 2020; Wang Y. et al., 2020, 2021).

TABLE 2

B/BMSY Stock status
≥1 Healthy
0.8–1.0 Slightly overfished
0.5–0.8 Overfished
0.2–0.5 Grossly overfished
≤0.2 Collapsed

The definition of the stock status based on the B/BMSY in the present study.

The relative biomass and first catch length estimated by LBB can be directly used to manage the stock with limited data, as follows (Wang Y. et al., 2020):

If relative stock size B/B0 is smaller than BMSY/B0 (B/BMSY < 1), the catches should be reduced;

If the mean length at first capture Lc is smaller than Lc_opt, then fishing can be started with a larger individual size.

Results

In this study, the stock resources of 19 Perciformes living in the Beibu Gulf were evaluated using the LBB method. The parameters Lmean/Lopt, Lc/Lc_opt, L95th/Linf, B/B0, B/BMSY, F/M, F/K, and Z/K were obtained (Table 3). The ratios Lmean/Lopt and Lc/Lc_opt were below one in 14 out of the 19 stocks, suggesting a truncated length structure and fishing of undersized individuals. The ratio of the 95th percentile length to asymptotic length L95th/Linf was close to one (>0.9) in 10 out of 19 stocks, suggesting that at least some large fish were still present. The ratio B/B0 was smaller than BMSY/B0 in 19 stocks, suggesting these fish species included in this study are being low biomass. Furthermore, the relative biomass (B/B0) for nineteen of the species in the Beibu Gulf evaluated here was 0.25 on average, which indicated a depletion rate of 75%.

TABLE 3

Scientific name Lmean/Lopt Lc/Lc_opt L95th/Linf B/B0 B/BMSY F/M F/K Z/K Assessment
Acropoma japonicum 0.84 0.8 0.82 0.32 0.89 1 1.5 3.09 Slightly overfished
Pennahia microcephalus 0.61 0.45 0.83 0.2 0.53 1.3 1.8 3.35 Overfished
Ariomma indica 0.97 0.95 0.9 0.24 0.66 1.7 2.5 3.96 Overfished
Branchiostegus argentatus 0.6 0.48 0.9 0.043 0.12 4.4 6.5 7.9 Collapsed
Decapterus maruadsi 0.72 0.6 0.91 0.28 0.77 0.99 1.6 3.11 Overfished
Parastromateus niger 0.75 0.69 0.94 0.053 0.15 5.5 9.1 10.8 Collapsed
Johnius belangerii 1 1.2 0.6 0.85 2.3 0.13 0.16 1.42 Healthy
Nemipterus japonicus 0.95 0.93 0.88 0.17 0.48 2.4 4 5.7 Grossly overfished
Nemipterus peronii 1.3 1.5 0.93 0.72 2 0.3 0.63 2.8 Healthy
Nemipterus virgatus 0.74 0.68 0.93 0.042 0.12 6.2 10 11.6 Collapsed
Evynnis cardinalis 0.89 0.84 0.98 0.065 0.17 5.9 7.8 9.08 Collapsed
Pennahia anea 0.92 0.88 0.83 0.24 0.64 1.6 2.1 3.4 Overfished
Pennahia pawak 0.82 0.75 0.99 0.34 0.94 0.88 1.4 2.93 Slightly overfished
Siganus fuscescens 0.8 0.74 0.82 0.12 0.33 2.8 3.9 5.36 Grossly overfished
Terapon theraps 0.91 0.86 0.96 0.09 0.25 4.3 7.2 8.88 Grossly overfished
Trachurus japonicus 1 1.1 9.2 0.43 1.2 0.88 1.2 2.55 Healthy
Trichiurus japonicus 0.65 0.55 0.86 0.049 0.13 4.6 6.8 8.3 Collapsed
Upeneus bensasi 1.1 1.2 0.91 0.37 1 1.2 1.9 3.58 Healthy
Upeneus moluccensis 1 0.98 0.96 0.17 0.49 2.4 4.9 6.98 Grossly overfished

Estimates of 19 fish species for 2011 given by LBB.

Figures 25 are the specific evaluation results of LBB method. The blue line in the figures represents the fit of the data and the LBB estimation, and the red line is the evaluation from the LBB method of population resources. Figure 2 shows similar results for five species. The LBB model gives a good fit. The parameter B/BMSY ranges from 0.12 to 0.17, and the estimated value of F/M is far greater than one. Therefore, the status of the stock of these five species (Branchiostegus argentatus, Parastromateus niger, Nemipterus virgatus, Evynnis cardinalis, and Trichiurus japonicus) is “collapsed.” The results for four similar species are shown in Figure 3. The estimated value of B/BMSY ranges from 0.25 to 0.49, and the estimated value of F/M is greater than 1. It is considered that the resource status of these four species (Nemipterus japonicus, Siganus fuscescens, Terapon theraps, Upeneus moluccensis) is “grossly overfished.” The results of six similar species are shown in Figure 4. The estimated values of the parameter B/BMSY range from 0.53 to 0.94, and the estimated value of F/M is close to 1. It is considered that the resource states of Acropoma japonicum and Pennahia pawak are “slightly overfished,” while Pennahia microcephalus, Ariomma indica, Decapterus maruadsi, and Pennahia anea are “overfished.” Finally, Figure 5 shows the results of four similar species where the parameter B/BMSY ranges from 1 to 2.3. Our assessment considers that the resource status of these species (Johnius belangerii, Nemipterus peronii, Trachurus japonicus, and Upeneus bensasi) is “healthy.”

FIGURE 2

FIGURE 2

The assessment results of five “collapsed” species with length-based Bayesian biomass (LBB) method in Beibu Gulf. The blue line (left) represents the fit of the data and the LBB estimation, and the red line (right) is the evaluation from the LBB method of stock resources. (A–E) Presents the result of Branchiostegus argentatus, Parastromateus niger, Nemipterus virgatus, Evynnis cardinalis, and Trichiurus japonicus, respectively.

FIGURE 3

FIGURE 3

The assessment results of four “grossly overfished” species with LBB method in Beibu Gulf. (A–D) Presents the result of Nemipterus japonicus, Siganus fuscescens, Terapon theraps, and Upeneus moluccensis, respectively.

FIGURE 4

FIGURE 4

The assessment results of two “slightly overfished” species and four “overfished” species with LBB method in Beibu Gulf. (A,B) Presents the result of Acropoma japonicum and Pennahia pawak, respectively. (C–F) Presents the result of Pennahia microcephalus, Ariomma indica, Decapterus maruadsi, and Pennahia anea, respectively.

FIGURE 5

FIGURE 5

The assessment results of four “healthy” species with LBB method in Beibu Gulf. (A–D) Presents the result of Johnius belangerii, Nemipterus peronii, Trachurus japonicus, and Upeneus bensasi, respectively.

Discussion

Most coastal fish populations in China cannot be evaluated comprehensively because of a lack of data (Liang et al., 2020). However, the LBB method can effectively evaluate the population with limited LF data (Ju et al., 2020a; Liang et al., 2020; Wang Y. et al., 2020, 2021; Zhang et al., 2020, 2021; Wang X. et al., 2021). The stock status was given in the LBB model based on the parameter B/BMSY, which had been described in detail in previous studies (Froese et al., 2018; Wang Y. et al., 2021).

In this study, the LBB method was used to evaluate the resource status of 19 Perciformes in the Beibu Gulf. The results showed that only 21% of the evaluated stocks were healthy and 79% were overfished. In particular, 26 and 21% of the assessed species were exhausted and severely overfished, respectively, while only 11 and 21% of the assessed species were slightly overfished and overfished, respectively. Zhang et al. (2021) assessed the resources of 10 species around the Nansha Islands, South China Sea. It was considered that the resources of 80% of the species assessed were overfished. According to Ju et al. (2020a), 80% of the five shark stocks living around Taiwan, South China Sea, were overfished; Zhang et al. (2020) evaluated 20 stock resources in Min River Estuary and found that 65% of the stock was overfished. The results of this study are consistent with these reports indicate most fish living in the South China Sea are facing overfishing pressures (Table 4). The ratio B/B0 was smaller than BMSY/B0 in all 19 stocks, suggesting the fish species included in this study are being low biomass. The relative biomass (B/B0) for the 19 species in the Beibu Gulf evaluated here was 0.25 on average, which indicated a depletion rate of 75%. This result was consistent with the 84% average depletion reported by Zhai and Pauly (2019). The ratios Lmean/Lopt and Lc/Lc_opt were below one in 14 out of the 19 stocks, suggesting a truncated length structure and fishing of undersized individuals. However, the ratio of the 95th percentile length to asymptotic length L95th/Linf was close to one (>0.9) in 10 out of 19 stocks, suggesting that at least some large fish were still present.

TABLE 4

Scientific name Assessment methods Study area Time Stock status This Study References
Acropoma japonicum None None None None Slightly overfished None
Pennahia microcephalus LBB Beibu Gulf 2006–2014 Overfished Overfished Wang Y. et al., 2021
Ariomma indica Electronic Length Frequency Analysis The South China Sea 2003 Overfished Overfished Huang and Chen, 2005
Branchiostegus argentatus Resource Survey The South China Sea 1993–1994; 1997–1999 Healthy Collapsed Wu and Xie, 2002
Branchiostegus argentatus Resource Survey Mid-Southern East China Sea 1994 Healthy Collapsed Lin et al., 1996
Decapterus maruadsi Electronic Length Frequency Analysis Beibu Gulf 1992–2012 Overfished Overfished Geng et al., 2018
Parastromateus niger Resource Survey The South China Sea 1972–1984 Healthy Collapsed Lu et al., 1986
Johnius belangerii None None None None Healthy None
Nemipterus japonicus Beverton-Holt Y/R Analysis Pakistan 2014 Healthy Grossly overfished Ali et al., 2014
Nemipterus peronii None None None None Healthy None
Nemipterus virgatus Schaefer Model; Fox Model; Schnute Model The South China Sea 2008–2017 Overfished Collapsed Wu et al., 2021
Evynnis cardinalis LBB Beibu Gulf 2006–2018 Overfished Collapsed Wang X. et al., 2020
Pennahia anea Resource Survey Northern South China Sea 2008–2009 Overfished Overfished Tuuli et al., 2011
Pennahia pawak Electronic Length Frequency Analysis Beibu Gulf 2008–2009; 2018–2019 Healthy Slightly overfished Yi et al., 2021
Siganus fuscescens None None None None Grossly overfished None
Terapon theraps None None None None Grossly overfished None
Trachurus japonicus Resource Survey Northern South China Sea 1997–1999 Healthy Healthy Chen and Qiu, 2004
Trichiurus japonicus YPR And SPR Sea Of Japan 2003–2011 Overfished Collapsed Watari et al., 2017
Upeneus bensasi Resource Survey Beibu Gulf 2007 Healthy Healthy Zhu et al., 2008
Upeneus moluccensis None None None None Grossly overfished None

Comparison of fishery resource assessment studies for 19 species.

In this study, five stocks (Branchiostegus argentatus, Parastromateus niger, Nemipterus virgatus, Evynnis cardinalis, and Trichiurus japonicus) had collapsed. Branchiostegus argentatus belongs to the warm-temperate fish, living in the middle and lower layers, and its maximum body length is 27.3 (see text footnote 1). In the 1990s, the resource status was healthy (Lin et al., 1996; Wang, 2002). However, because the mesh size used is less than 5 cm, its larvae are also caught in large quantities (Lin et al., 1996). With the increase in fishing intensity, the stocks of Branchiostegus argentatus are almost exhausted. Parastromateus niger is a pelagic fish that migrates in warm water in the open sea. It is one of the fish species with high economic value in the South China Sea. Its stock resources were rich from 1972 to 1984, but with the increasing catch (Lu et al., 1986), the resources by 2011 were overburdened, and the biomass was at a very low level. Nemipterus virgatus is one of the five major economic fishes in the northern South China Sea. Overfishing occurred in the 5 years from 2008 to 2017, especially in 2012, which was consistent with our assessment results (Wu et al., 2021). Evynnis cardinalis is mainly distributed in the South China Sea and the South East China Sea and is one of the important species for the bottom trawl fishery. Wang X. et al. (2020) evaluated the stock resources in Beibu Gulf from 2006 to 2018 by the LBB method, and the results showed that the resources were overfished, especially in 2010 and 2011, which is consistent with our evaluation. Trichiurus japonicus is a warm water pelagic fish, which is one of the most valuable fish species in the northern South China Sea.

Four stocks (Nemipterus japonicus, Siganus fuscescens, Terapon theraps, and Upeneus moluccensis) are grossly overfished. Nemipterus japonicus is widely distributed through the Indian Ocean and West Pacific. Ali et al. (2014) analyzed the population resources in the Indian Ocean from 1986 to 2014, but not in the South China Sea. Similarly, although Siganus fuscescens, Terapon theraps, and Upeneus moluccensis occupy an important economic position in China’s fisheries (Ma and Liu, 2006), the specific assessment of their resources has not been reported before.

The resource status of four stocks (Pennahia microcephalus, Ariomma indica, Decapterus maruadsi, and Pennahia anea) is overfished. Pennahia microcephalus is widely distributed in the Indo-West Pacific tropical regions, including the East China Sea and the South China Sea. It is one of the dominant commercial fish species throughout the coastal area of Southeast China (Yan et al., 2009). Wang M. D. et al. (2021) used the LBB method to evaluate its resource status in the Beibu Gulf. The results showed that the white croaker was overfished from 2006 to 2014, especially after 2009, which was consistent with the results of this study. Ariomma indica is a bottom fish, living in warm water. It is one of the most common economic fish in the South China Sea and also the main fishing target of bottom trawlers in the South China Sea (Lin, 2003). Decapterus maruadsi is one of the most common croakers currently on retail sale in Hong Kong, and its resources were overfished in 2008–2009 (Tuuli et al., 2011).

In this study, two stocks (Acropoma japonicum and Pennahia pawak) were slightly overfished, and four stocks (Johnius belangerii, Nemipterus peronii, Trachurus japonicus, and Upeneus bensasi) were healthy. Acropoma japonicum is one of the dominant species in the Beibu Gulf (Zhang et al., 2016; Cai et al., 2018), but there are few reports on its stocks. Pennahia pawak is a relatively stable resource species in the Beibu Gulf, which has important ecological status and economic benefits. On the basis of the analysis of fishery biology, Yi et al. (2021) thought that the resources of Pennahia pawak were lightly exploited. Johnius belangerii is one of the main economic species of fishing in China. With the overfishing of offshore waters, its resources have begun to decline (Guo et al., 2017). Nemipterus peronii is widely distributed in the Indo Western Pacific, from the Red Sea to Taiwan and northern Australia, and its maximum body length is 29 cm (see text footnote 1). Trachurus japonicus is one of the main upper middle economic species in the northern South China Sea, and its resource status was healthy from 1997 to 1999 (Chen and Qiu, 2004). Upeneus bensasi is one of the main economic fishes in Beibu Gulf of China. Its resources were in a healthy state in 2008 (Zhu et al., 2008).

The Bayesian estimation model based on body length (LBB) is a new method to analyze the LF data of economic fishery catches (Froese et al., 2018). The advantages of the LBB model are as follows: (1) the results of relative biomass or stock state have been verified by simulation and actual stocks; (2) there is no significant difference between the predicted LBB and the simulated B/B0; (3) the prediction of stock status by LBB is similar to that of other models; (4) LBB makes a preliminary estimation of the status of the fish group according to the LF data of the fishery; and (5) the results of LBB provide objective B/B0 priors for other evaluation methods such as CMSY and AMSY (Froese et al., 2017, 2018). The LBB method only needs body length and frequency to evaluate the fish resources in a certain region, which solves the problem that some regions cannot evaluate the fishery germplasm resources owing to the lack of available data. However, the LBB model is not always accurate because it only inputs length and frequency data. If the LBB method is combined with other models, the results will be more reliable (Wang Y. et al., 2020, 2021).

Conclusion

The stock status of 19 species of Perciformes living in the Beibu Gulf was evaluated by the LBB method. Among the 19 fish stocks assessed, 15 were overfished and only 4 were healthy. The resources of Branchiostegus argentatus, Parastromateus niger, Nemipterus virgatus, Evynnis cardinalis, and Trichiurus japonicus have collapsed because of long-term overfishing, and the existing biomass is at a low level. Fishery managers need to take specific measures, such as limiting the size of fishing nets and reducing the operation time of fishing vessels, to restore fishery resources. However, the resource status of Johnius belangerii, Nemipterus peronii, Trachurus japonicus, and Upeneus bensasi is relatively healthy, and the population development rate is relatively low. There is still room for development of these fisheries. Therefore, we can appropriately increase the catch of these populations, so as to reduce the fishing pressure on depleted fish species in the South China Sea. Although LBB can easily and quickly evaluate the status of fishery resources, the assessment results may not be accurate because only the frequency of fish body length is used. It needs to be combined with other models or methods to obtain more accurate resource assessment results.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Statements

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

Ethics statement

The animal study was reviewed and approved by Guangdong Ocean University.

Author contributions

GH and HZ analyzed the LF data and completed the first draft. HZ provided guidance on data analysis and structure of the manuscript. JW, YC, and JL provided suggestions on the revision of the manuscript. JW, YC, and JL helped to collect the original length data. All authors are contributed to revise the manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (Nos. 42090044 and 31702347), the Strategic Priority Research Program of the Chinese Academy of Sciences (No. XDB42000000), Youth Innovation Promotion Association CAS (No.2020211), and the start-up project of Guangdong Ocean University (No. R19006).

Acknowledgments

We thank numerous colleagues for their generous support of this study and thank the editor and reviewers for their constructive suggestions to our work.

Conflict of interest

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

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars.2021.731837/full#supplementary-material

Footnotes

1.^ www.fishbase.org

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Summary

Keywords

Beibu Gulf, LBB method, overfishing, stock assessment, fishery resources

Citation

Hou G, Zhang H, Wang J, Chen Y and Lin J (2021) Stock Assessment of 19 Perciformes in the Beibu Gulf, China, Using a Length-Based Bayesian Biomass Method. Front. Mar. Sci. 8:731837. doi: 10.3389/fmars.2021.731837

Received

28 June 2021

Accepted

10 August 2021

Published

27 August 2021

Volume

8 - 2021

Edited by

JInghui Fang, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences (CAFS), China

Reviewed by

Martina Scanu, University of Bologna, Italy; Siquan Tian, Shanghai Ocean University, China

Updates

Copyright

*Correspondence: Hui Zhang,

This article was submitted to Marine Fisheries, Aquaculture and Living Resources, a section of the journal Frontiers in Marine Science

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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