Research Article

Stock’s Status of Elongate Glass-Perchlet Chanda nama in the Ganges River (Bangladesh): Suggestions for Future Proper Management

Md. Asadujjaman1, Md. Yeamin Hossain2*, Most. Farida Parvin3, Most. Shakila Sarmin2, Fairuz Nawer2, Wasim Sabbir4, Md. Ashekur Rahman2, Nur-E-Farjana Ilah2, Md. Joynal Abedin5, Md. Abdus Samad6 and Gitartha Kaushik7

1Department of Aquaculture, Khulna Agricultural University, Khulna 9100, Bangladesh; 2Department of Fisheries, University of Rajshahi, Rajshahi 6205, Bangladesh; 3Institute of Environmental Science (IES), University of Rajshahi, Rajshahi 6205; Bangladesh; 4Fisheries and Marine Resource Technology Discipline, Khulna University, Khulna 9208, Bangladesh; 5Department of Zoology, Carmichael College, National University, Bangladesh; 6Department of Fisheries and Marine Bioscience, Jashore University of Science and Technology, Jashore 7408, Bangladesh; 7Department of Zoology, Rangapara College, Sonitpur, Assam 784505, India.

Received | December 08, 2022; Accepted | December 18, 2023; Published | March 22, 2024

*Correspondence | Md. Yeamin Hossain, Department of Fisheries, University of Rajshahi, Rajshahi 6205, Bangladesh; Email: hossainyeamin@gmail.com

Citation | Asadujjaman, M., M.Y. Hossain, M.F. Parvin, M.S. Sarmin, F. Nawer, W. Sabbir, M.A. Rahman, N.F. Ilah, M.J. Abedin, M.A. Samad and G. Kaushik. 2024. Stock’s status of elongate glass-perchlet Chanda nama in the Ganges River (Bangladesh): Suggestions for future proper management. Sarhad Journal of Agriculture, 40(2): 275-285.

DOI | https://dx.doi.org/10.17582/journal.sja/2024/40.2.275.285

Keywords | Chanda nama, Ganges River, Management, Mortality, Stock assessment

Copyright: 2024 by the authors. Licensee ResearchersLinks Ltd, England, UK.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Introduction

Fish are considered the most important source of animal protein worldwide (Roy et al., 2020). In open-water habitats, the increasing demand for fish and fisheries products results from immense pressure on their natural stocks (Sabbir et al., 2021). Fish are currently known as inadequate renewable resource (Panhwar et al., 2013). Therefore, sustainability is obligatory to maintain the renewable capability of the wild fisheries stock by the appropriate assessment of the exploitation rate. About 2,000 species were recorded from freshwater under the order of Perciformes (Froese and Pauly, 2022). Around 8 genera and 51 species are covered by the family Ambassidae (Nelson, 1994) including Chanda nama Hamilton, 1822. This species is popularly known as the semi-transparent-body ray-finned fish. Further, this species has a wide range of distribution from Bangladesh, Myanmar, India, Pakistan to Nepal (Roberts, 1994). Globally C. nama is identified as the name of Elongate glass-perchlet whereas in Bangladesh and India, it is popular as Chanda or Nama chanda and in Nepal as Nata channa or Chanerbijuwa (Froese and Pauly, 2022). It inhabits clear streams, static and flowing waters, ponds, canals, and flooded fields (Rahman, 1989). It is a very popular ornamental cum food fish for rural people of south-east Asia and provides a source of nutrition with a low market price. Earlier, C. nama in Bangladesh was evaluated as vulnerable (IUCN Bangladesh, 2000) and now it is categorized as the least concern (IUCN, 2021).

Understanding the life history characteristics of a particular fish population is necessary to ensure sustainability in the wild environment (Foster and Vincent, 2004). However, the study gap of the life history traits of fish populations in the open water ecosystem is a major problem to execute proper fishing policies in the wild ecosystem and it requires immediate investigation (Sabbir et al., 2021). Stock assessment of fish allows us to ensure appropriate management of natural fish stock by providing baseline information. Observation of the growth pattern for a particular species is significant to analyze the seasonal variation of growth rate, and condition indices and to estimate biomass as well as production (Sabbir et al., 2021; Mawa et al., 2022; Nadia et al., 2022). Dynamic models (Beverton and Holt, 1957) help us in determining potential yields and stock biomass, which are helpful to define management strategies comprehensively. For deriving these models, knowledge of growth, recruitment, mortality, MSY, and exploitation rate of fish stocks is essential. However, stock assessment through length-based methodology is effective in studying fish population parameters in open-water habitats (Pauly and Morgan, 1987). Moreover, knowledge about length-frequency distribution (LFD) is crucial to detect the health of waterbody by stock assessment of existing biomass (Ranjan et al., 2005; Sabbir et al., 2022).

A few research have been carried out on different aspects of C. nama, particularly feeding ecology (Grubh and Winemiller, 2004), length-length and length-weight relations (Hossain et al., 2012, 2016; Islam et al., 2017), life-history considerations (Hossain et al., 2021a) but study on stock assessment is not available. Because of the inadequacy of biotic knowledge, the current investigation was conducted to describe the population dynamics of economically valuable C. nama. We analyzed the growth parameters, mortality rate, MSY, recruitment, and relative yield per-recruitment of C. nama with one year of sampling which covers small to large sizes in the Ganges River.

Materials and Methods

Sampling and measurement

The experiment has been carried out in the Ganges River (24° 65’ N and 88° 06’ E), north-western Bangladesh. 1260 samples of C. nama were taken from the fisherman’s catch through January-December 2017 using the gill net (mesh size: 1.5-2.5 cm). Fish were immediately iced at the sampling sites and then kept with 10% formalin for further study. Measurements of the individual’s total length (TL, cm) and body weight (BW, g) were recorded with a measuring board and digital balance, accordingly. However, only TL was utilized for the estimation of the stock through stock assessment tools FiSAT II (FAO-ICLARM) (Gayanilo and Pauly, 1997).

Growth pattern and parameters

The growth pattern was determined using the equation BW = a*(TL)b where a and b were analyzed from ln (W) = ln (a) + b*ln (L) (Froese, 2006). To verify isometric or (±) allometric growth (Tesch, 1971), the t-test has been considered. The Powell-Wetherall method was followed to analyze the length-frequency distribution (Wetherall, 1986) through the FISAT software (Gayanilo et al., 1994). This assisted an adjustment of the length-based Z-equation of Beverton and Holt (1956) into a form of Ĺ - L’a + Lb (L’ = cut-off length, as the length for each size class of the smallest recruited fish), Ĺ = (L∞ + L’)/[1+(Z/K)] indicates the mean length of all fish ≥ L’. An initial L∞ was obtained from s/b and Z/K as – (1+b)/b through the above equation. Depending on the size range captured for the species, the frequency of the size-class intervals was used. The length-frequency dataset was arranged to assess von Bertalanffy growth function (VBGF) such as asymptotic length (L∞) and growth constant (K) by FiSAT software with the ELEFAN I tools (Gayanilo et al., 2005). The life-span (tmax) was evaluated with log tmax = 0.5496 + 0.957*log(tm) where tm means the age of first sexual maturity (Froese and Binohlan, 2000). Following the Log (-t0) = -0.3922 - 0.2752 Log L∞ - 1.038 Log K, age at zero length (t0) was computed (Pauly, 1980). Whereas the growth performance index was evaluated via Ø’ = log10K + 2log10L∞ (Pauly and Munro, 1984).

Mortality, exploitation and recruitment

The total mortality rate (Z) was obtained through the length converted catch curve procedures. The natural mortality (M) was computed by the empirical formula (Pauly, 1980) using growth parameters: log10M = −0.0152 − 0.279 log10L∞ + 0.6543 log10K +0.4634 log10T; where T signifies the average annual ambient temperature (oC). The mortality by fishing (F) was obtained from Z-M. Furthermore, the exploitation rate (E) was estimated by E = F ⁄ Z = F ⁄ (F + M) (Gulland, 1983). The recruitment pattern was determined with growth parameters, where plots revealed the seasonal trends of fish recruitment. Recruitment patterns specified by the VBGF frequencies and reconstructed samples were used.

Relative yield-per-recruit (Y’/R) and maximum sustainable yield (MSY)

Beverton and Holt’s (1979) concept has been followed to estimate Y′/R of C. nama. Emax, E0.1 and E0.5 were obtained from the Y’/R vs. E model. At the E0.5 stage, the length of the first capture (Lc) was suggested. Using the length-structured VPA routine, the steady state biomass (SSB) was computed. As a consequence, the MSY of C. nama was determined through the equation of Gulland (1983) as 0.5*SSB*Z.

Results and Discussion

Growth pattern and parameters

Table 1 presented monthly descriptive information on the length and weight of C. nama. Additionally, variables a and b of LWR were inferred from the growth data and the correlation was defined through W = 0.0071TL3.13 (Figure 1). The Powell-Werherall technique combined and evaluated monthly length frequency data with the expected findings: L∞ = 7.56 along with Z/K = 2.92 (Figure 2). Further, the K-scan method generated L∞ as TL of 10.25 cm whereas the K value was 0.55 year-1 (Table 2 and Figure 3). The growth curves (von Bertalanffy) were illustrated in Figures 4 and 5. The t0 was assessed as 0.057 years, while the Ø’ was 1.762 and tmax was estimated as 2.49 years (Table 2).

 

Table 1: Descriptive statistics on the total length (cm) and body weight (g) measurements of Chanda nama Hamilton, 1822 in the Ganges River of north-western Bangladesh during January–December 2017.

Month	n	TL				BW
		Min	Max	Mean ± SD	95% CL	Min	Max	Mean ± SD	95% CL
Jan	101	2.1	6.7	4.251±0.970	4.060 to 4.443	0.07	3.25	0.820±0.643	0.693 to 0.946
Feb	121	2.6	7.3	4.360±0.095	4.171 to 4.548	0.11	3.84	0.866±0.657	0.747 to 0.984
Mar	108	2.1	8	4.969±0.952	4.788 to 5.151	0.05	4.64	1.048±0.691	0.917 to 1.180
Apr	106	3	5.8	4.057±0.520	3.956 to 4.157	0.25	1.82	0.622±0.276	0.569 to 0.675
May	107	2.6	5.4	4.185±0.610	4.061 to 4.302	0.15	1.6	0.717±0.320	0.655 to 0.778
Jun	137	2.9	6.3	4.747±0.547	4.654 to 4.839	0.24	2.36	1.015±0.340	0.957 to 1.072
Jul	104	2.2	6.2	4.401±0.746	4.256 to 4.546	0.06	2.14	0.795±0.418	0.713 to 0.876
Aug	102	2.2	6.3	4.109±0.760	3.959 to 4.258	0.07	2.31	0.677±0.376	0.603 to 0.751
Sep	107	1.7	5	3.052±0.769	2.905 to 3.200	0.05	1.2	0.318±0.246	0.270 to 0.365
Oct	80	2.2	6.5	4.156±1.324	3.861 to 4.451	0.04	2.8	0.864±0.797	0.686 to 1.041
Nov	99	2.7	6.3	4.119±0.721	3.975 to 4.263	0.17	2.31	0.659±0.389	0.582 to 0.736
Dec	88	3	7.3	4.903±1.213	4.646 to 5.160	0.19	3.5	1.243±0.947	1.043 to 1.444

 

 

 

 

 

 

Table 2: Growth parameters (L∞ and K), mortality (Z, M, F) and Fishery parameters (E, Lc, and MSY) of Chanda nama Hamilton, 1822 in the Ganges River of north-western Bangladesh.

Description of parameters	Values
Growth and reproduction
Asymptotic length (L∞)	10.25 cm TL
Growth coefficient (K)	0.55 year-1
Life-span (tmax)	2.49 years
Growth performance indexes (Ø')	1.762
Age at zero length (t0)	0.057 years
Size at first sexual maturity (Lm)	5.11 cm TL
Age at first sexual maturity (tm)	0.69 years
Mortality parameters
Total mortality (Z)	3.11 year-1
Natural mortality (M),	1.63 year-1
Fshing mortality (F)	1.48 year-1
Fishery parameters
Exploitation (E)	0.48
Emax	0.46
E0.1	0.37
E0.5	0.27
Total length at first capture (Lc)	3.32 cm TL
Maximum sustainable yield (MSY)	4.51 metric tons

 

 

Mortality and recruitment

The assessed Z, F, and M were 3.11, 1.48, and 1.63 year-1, respectively (Figure 6 and Table 2). The pattern of recruitment for C. nama population was mostly continual. The spawning activity was expected to begin in February and continue within September, while its main recruitment season coincided with the major spawning period between the month of May and July with only a peak during July (15.28 percent), suggesting a strong seasonal recruitment pattern (Figure 7).

 

Relative yield-per recruits (Y’/R) and maximum sustainable yield (MSY)

The calculated Emax was 0.46, while the E0.1 and E0.5 were 0.37 and 0.27, according to the Y’/R analysis (Figure 8 and Table 2). The recommended exploitation rate (E) was found 0.48 (Figure 9). Further, the optimum TL at the first capture (Lc = Lc50) was determined as 3.32 cm for C. nama (Figure 10). From the VPA analysis (Figure 11), the approximate SSB was 2.90 metric tons. Therefore, the MSY was calculated as 4.51 metric tons, when the required length (Lc = 3.32 cm TL) is sustained at first capture.

 

 

 

Stock assessments are considered to understand the growth, birth, and mortality of a fish, which is helpful for fish stock predictions to select the management approach (Hilborn and Walters, 1992). There is no information in the literature on the stock status of C. nama. Individuals of different sizes were captured throughout the year from the Ganges River using regular fishing gears. In this research, it was not possible to collect samples larger than 8 cm sized and 4.64 g weighed, which can be accounted for the selection of fishing tools instead of their disappearance from fishing areas or fishers did not catch where larger sizes reside (Hossain et al., 2017; Nawer et al., 2017; Parvin et al., 2021; Sarmin et al., 2021a).

 

Table 3: Population number (N× 104) by size (TL) and steady state biomass (SSB) of Chanda nama at different levels of fishing mortality (F) in the Ganges River of north-western Bangladesh.

Mid-length	Population (N× 104)	Fishing mortality (F)	Steady state biomass (SSB) metric tons
1.5	48347300	0.0238	0.05
2	40712576	0.0635	0.12
2.5	33779904	0.2075	0.21
3	27227948	0.4149	0.31
3.5	21067352	0.9509	0.39
4	14879196	1.5007	0.44
4.5	9434261	2.1656	0.40
5	5175191	2.5363	0.32
5.5	2514054	1.7155	0.24
6	1324466	2.0986	0.17
6.5	596018	1.8408	0.11
7	256625.6	1.9921	0.06
7.5	92984.63	0	0.05
8	54168.49	0.704	0.03
8.5	21013.51	1.48	0.02
Total SSB			2.90

 

 

The highest length of C. nama was recorded at 8 cm in the present study which exceeded previous records of 7.0 cm from Deepor beel Assam, India (Borah et al., 2017), 7.4 cm from the Brahmaputra River (Islam et al., 2017), and 7.5 cm from the Mathabhanga River in Bangladesh (Hossain et al., 2021a). But our observed TL was smaller than 11.0 cm found by Menon (1999). Each of those values varied from our observed values, which could be due to natural causes such as water temperature, food sources, and differences in geographic location (Hossain and Ohtomi, 2010). The allometric factor b can vary from 2 to 4, but values range from 2.5 to 3.5, which are more standard (Froese, 2006). The b value of LWR was 3.13 in this study, indicating positive allometric growth. However, a negative allometric growth was found (b = 2.79) by Hossain et al. (2012) from the Jamuna River, b = 2.87 was observed from the Brahmaputra River (Islam et al., 2017), and b = 2.80 from Deepor beel, Assam, India (Borah et al., 2017) for C. nama. Hossain et al. (2016) verified the isometric growth (b = 3.0) in the Ganges River, Bangladesh. The variation of growth pattern related to gonad ripeness, fish health, seasonal stomach contentment, sex, preservation process, and difference in size group (Hossain et al., 2018; Rahman et al., 2020; Tanjin et al., 2020; Hossain et al., 2021b; Sarmin et al., 2021b, 2022).

The growth parameters were analyzed to predict the stock biomass and future yields at multiple stages of fishing tactics, which are widely helpful to define different management practices. The calculated L∞ was 10.25 cm when the K was 0.55 year-1. We noted L∞ was greater than our biggest fish found. A number of researchers (Gordoa and Moli, 1997; Macpherson, 1998; Vigliola et al., 1998) explained the reverse state where the model of von Bertalanffy is not enough to describe the growth of the Sparidae family due to the fast growth during the first year of life and noticeably decelerating thereafter. It is important to approach growth assessment from a multivariate perception, where both L∞ and K need to be observed. The growth performance index (Ø’) was also used to measure and display the least variation related to other available indices (Pauly and Munro, 1984). For C. nama, Ø’ was recorded as 1.762 in this study. We have found the longevity or life span (tmax) for the species which was 2.49 years and t0 was found to be 0.057 year. In the old technique, a variety of specimen characteristics (sample sizes and variation of sizes) and regional variations are likely to be due to the divergence in growth parameters (Monteiro et al., 2006). The previous study was unavailable in the literature, so it was not possible to compare these parameters.

The natural mortality was assessed as 1.63 years-1 while the fishing mortality was 1.48 years-1. Natural fish mortality is due to non-fishing causes like diseases, predation, cannibalism, competition, lack of food, stress of spawning and impact of pollution (Yongo and Outa, 2016). When observing the biological characteristics (fast-growing, small), it may be considered rational (Dulcic´ et al., 2007). In our study, we have found the main cause of higher natural mortality is predation. To signify the influence on yield of variations in exploitation (E) with the critical-length ratio (Lc/L∞), we have been using yield isopleths (Figure 9). As far as the fishing regime is concerned, it implies fish are exploited at a low level of effort in regard to their relative yield per recruit (King and Etim, 2004). We assessed a lower maximum acceptable exploitation rate (Emax = 0.46) from the current exploitation level E = 0.48. Thus, in the Ganges River, this species is starting to face overexploitation. Further, the Z/K ratio was recorded as 2.92 (Figure 2), which indicated a slightly greater degree of exploitation.

The length at first capture (Lc50), asymptotic length (L∞), and optimum length (Lopt) values will be utilized to identify the extent of the exploited population for proper assessment of the valuable fishery (Akélé et al., 2015). If the juveniles are mostly caught then the Lc/L∞ values are less than 0.5 (Pauly and Moreau, 1997). This also implied that the first capture size (Lc) was smaller than the optimum size (Lopt). A 50 percent probability of capture was 3.32 cm (Lc50) and we found L∞ as 10.25 cm in the present investigation. As a result, the Lc/L∞ ratio was 0.32 which is less than 0.5 and signifies the dominancy of the very small individuals in the Ganges River.

Recruitment patterns can be illustrated with a graph showing variations in recruitment frequency over time (King and Etim, 2004). As a result, the supply of food and environmental conditions may have an impact on recruitment. There was a main recruitment peak in this population in one year, primarily from May to July, and it intersected in time to provide a constant year-round trend (Figure 7). Moreover, the calculated MSY of C. nama from the Ganges River was 4.51 metric tons, when the required size of 3.32 cm (Lc) is managed at first capture.

Conclusions and Recommendations

Our study highlighted the stock information comprising growth, mortality, recruitment, and exploitation rate of C. nama. Overfishing might be a notable threat to the wild population as Emax = 0.46 is very close to E = 0.48. To ensure justifiable management of C. nama population in the Ganges River, illegal gear must be excluded. Besides, the mesh size needs to be increased to stop the harvesting of the small mature fish. However, to ensure a proper strategy for the management purpose, these findings might be operative in Bangladesh or elsewhere.

Acknowledgements

We wish to expand our heartfelt gratitude to (i) TWAS for research grants (Ref: RGA No. 14-028 RG/BIO/AS_1; UNESCO FR: 324028574) (ii) BARC, PIU, NATP-2, Sub-project ID: 484 for technical and financial assistance.

Novelty Statement

This study is the first record on stock assessment of Chanda nama from the Ganges River, Bangladesh as well as from worldwide. The information of this research would be effective for regulating early management policies to ensure the sustainable production of this species.

Author’s Contribution

Md. Asadujjaman: Instructed to write the manuscript.

Md. Yeamin Hossain: Developed the idea and methodology.

Most. Farida Parvin: Wrote the manuscript.

Most. Shakila Sarmin: Edited and formatted the manuscript.

Fairuz Nawer: Carried out data analyses.

Wasim Sabbir: Helped in revision and edition of the manuscript.

Md. Ashekur Rahman: Executed sampling and data collection and laboratory work.

Nur-E-Farjana Ilah and Md. Joynal Abedin: Assisted in laboratory work.

Md. Abdus Samad: Reviewed the manuscript.

Gitartha Kaushik: Given constructive comment on our manuscript.

Conflict of interests

The authors have declared no conflict of interest.

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