Population Dynamic Parameters of Rohu, Labeo rohita (Hamilton, 1822) in the Indus River, Sindh, Pakistan
Memon Aamir Mahmood1,2, Du Xin3, Chang Muhammad Saleem4,5, Chen Zhu4, Xu Xiaona4, Yelin Jiang4 and Liu Qun1*
1College of Fisheries, Ocean University of China, Qingdao, 266003, Shandong, China
2Sindh Fisheries Department, (Marine Wing), Karachi, 74400, Sindh, Pakistan
3Ocean College, Hebei Agricultural University, Qinhuangdao, 066003, Hebei, China
4Fisheries Research Institute, Anhui Academy of Agricultural Sciences, Anhui Key Laboratory of Aquaculture and Stock Enhancement, Hefei 230031
5Department of Science & Technical Education, University of Sindh Jamshoro, 76080, Sindh, Pakistan.
ABSTRACT
The population dynamics of Labeo rohita in the Indus River of Pakistan were analyzed using monthly length frequency data from January 2013 to December 2013. The study focused on growth, mortality rates, exploitation, biological reference points (BRPs), yield per recruit, and growth performance index. A total of 720 fish samples ranging from 15 to 35cm in length (average length of 23±5.111cm) and weighing 50 to 700g (average weight of 225±144g) were collected. The relationship between length and weight was determined as W= 0.025 L2.844 with R2= 0.990. The von Bertalanffy growth model parameters were L∞= 36.75cm and K= 1.200 yr-1, t0= - 0.904 years and Rn= 0.313. The natural mortality rate was 1.662 yr-1, total mortality was 2.06 yr-1 with CI95% 1.65-2.46yr-1 (r2= 0.895), fishing mortality was 0.398 yr-1, and current exploitation ratio was 0.193. Growth performance indices for asymptotic length Φ’= 3.210 yr-1 and asymptotic weight Φ= 1.979 yr-1 were calculated. The Beverton-Holt yield per recruit model was done by FiSAT-II in which tc was 1, Fmax 3 yr-1 and F0.1 2.1 yr-1. The current age at the first capture was approximately 1 year, Fcurrent 0.398 yr-1 was smaller than Fmax and F0.1 and current fishing mortality 0.398 yr-1 is smaller than the target biological reference point Fopt = 1.662 yr-1, Fmax 3 yr-1 and F0.1 2.1 yr-1 indicating the stock of the Labeo rohita in Indus River is not overfished. The estimated parameters suggest that the fishery of Labeo rohita in the Indus River can be managed sustainably.
Article Information
Received 29 December 2023
Revised 10 March 2024
Accepted 26 March 2024
Available online 02 October 2024
(early access)
Published 24 September 2025
Authors’ Contribution
MAM, LQ Writing the original manuscript, designing the experiment, generating funds, reviewing and editing, visualization, resources, validation, formal analysis, and data curation. DX and MSC participated in the writing manuscript, data curation, conceptualization, methodology, Writing review and editing, and data analysis. CZ, XX and YJ participated in manuscript writing.
Key words
Labeo rohita, Sustainable management, Overfishing, BRPs, FiSAT
DOI: https://dx.doi.org/10.17582/journal.pjz/20231229182844
* Corresponding author: [email protected]
0030-9923/2025/0006-2611 $ 9.00/00
Copyright 2025 by the authors. Licensee Zoological Society of Pakistan.
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
The Indus River plays a crucial role as Pakistan’s primary water route and a significant geographical element of the Indus civilization, which marked the early urbanization period in the Indian subcontinent between 2500 and 1900 BCE (Before Christ Era). Initially known as Sindhu, the river’s name influenced the name of the Pakistani province of Sindh. The change from Sindhu to Indus is a minor phonetic alteration, and India derived its name from the Indus River (Indus River, 2012). The Indus River is the single most important natural resource in Pakistan and the Kotri Barrage is one of the most important fishing centres along the Sindh over the lower reaches of the river Indus (Bhatti, 1999). Kotri Barrage was built in 1955 (Mushtaq, 1975) and is located on the right bank of the Indus River. It lies at 25º 26’ N and 68º 22’ E and is the last barrage on the Indus River measuring about 0.575 miles (920 m) across the Indus River, near Hyderabad city in southern Pakistan; the river runs about 100 km below (Bhatti, 1999) before discharging into the Arabian Sea (Yu et al., 2013).
Pakistan has one of the largest integrated irrigation network systems in the world in the Indus Basin during the current century. It serves 34.5 million acres of contiguous cultivated land along with the Indus River and its major tributaries. The total length of the Indus River is 2900 km with a drainage area of about 966,000 sq. km. The system has three major storage reservoirs namely Tarbela and Chasma on the Indus River while the Mangla dam is on the Jhelum River. There are 19 Barrages/headwork, 12 link canals, 45 canal commands measuring 58,450 km in length and some 99,000 watercourses measuring 160,000 Km in length (Kahlown and Majeed, 2003).
The reported number of freshwater and marine water fish species is 193 and 326, respectively from water bodies of Pakistan (Rafique, 2007; Psomadakis et al., 2015). Similar to marine fisheries, inland fisheries of Pakistan have a tremendous capacity for holding aquatic animal diversity including fish, crustaceans and Molluscs. Pakistan has extensive inland water areas, which depend on the water type body that has much more potential for development both in inland fisheries and aquaculture. The Indus River is dominated by freshwater resources such as rivers, lakes, ponds and reservoirs (FAO, 2009).
The agricultural sector has remained an important element of Pakistan’s economy. This agriculture sector accounts for 19.30% of the overall Gross Domestic Product (GDP) in Pakistan and this industry adds value to the economy by creating 45% of employment in rural areas (PES, 2019-20). In Pakistan, fishery plays an important role in the economy and is considered a reducing poverty tool towards the economic growth of the country. The fisheries industry made a 0.4% contribution to the GDP and brought in foreign exchange through exports totaling US $ 317.307 million (Rs 49,528 million) in the 2019-20 financial year (PES, 2019-20). Pakistan’s export of fish and fishery products saw positive growth in 2019-20. A total of 133,226 metric tonnes were exported, with a value of $317.307 million (Rs 49,528 million). The main buyers of Pakistan’s fish and fishery products were China, Thailand, Malaysia, the Middle East, Sri Lanka, and Japan. Comparing the export figures to the previous year 2018-19, there was a 2.7 per cent increase in quantity, an 8.0 percent increase in value, and a significant 26.2 percent increase in rupee terms. This indicates a successful performance in the export of fish and fishery products during the 2019-20 period. The provided text highlights the production of marine and inland fish during 2019-20. The total combined production of fish during this period was 701,726 metric tonnes. Out of this total, 474,025 metric tonnes were sourced from marine waters, while the remaining quantity came from inland waters (PES, 2019-20). Mainly more than 80% of the total inland fisheries production comes from rivers and reservoirs. Sindh province contains more than 100 natural lakes, which are good sources of fish fauna. The major contribution of the freshwater fishing system is the Indus River and its tributaries (FAO, 2009).
Cyprinidae is an important family of freshwater fishes distributed all over the world in 371 genera with 3036 species (Eschmeyer and Fong, 2016). This family is represented by 74 species in Pakistan and considered as largest freshwater fish fauna family in terms of genera and species (Mirza, 2003). The genus Labeo is the largest genera in Pakistan and is represented by 15 species (Mirza, 1975). The species of this family have significance in aquaculture and high commercial importance in inland fish fauna species of Pakistan (Peter, 1999).
Labeo rohita is one of the most important species of the inland fisheries in Pakistan, which contributes around 35% of total stocking, and 23% of the total aquaculture production in the region (Ashraf and Zafar, 2013). This common freshwater teleost fish Labeo rohita (Hamilton, 1822) is commonly known as “Roho Labeo” and locally known as “Rohu” or “Dumbra” in Pakistan (Ali, 1999). It is an esteemed table fish, has high commercial and aquaculture importance, and is a geographically widespread species in tropical freshwater of India and adjacent countries with considerable variation in reproductive traits (Chondar, 1999). The natural resources of the fish are from the network of the Ganges, Sindh and Brahmaputra River systems in the north, and the east and west coast river systems flowing through south and central India (FAO, 2011). This freshwater fish species is naturally distributed well in the rivers, lakes and ponds of Pakistan, Bangladesh, India, and Myanmar (Talwar and Jhingran, 1991) and also reported from brackish-water systems (Riede, 2004). This is the column feeder fish and mostly feeds on phytoplankton and soft weeds. The fish L. rohita is one of the most important economic food fish in Pakistan and is considered as tastiest of all carp. This species breeds during summer (July-August) in naturally flooded riverine areas of Pakistan and grows up to a length of 1.2 m (Ali, 1999), while the maximum length of this fish is reported at 200 cm (Frimodt, 1995).
The relationship between humans and riverine is intricate and has developed over millions of years, showcasing our dependence on riverine fisheries for resources and climate regulations (WHO, 2018). Riverine fisheries play a crucial role in the cultural and economic aspects of many communities globally. These fisheries are essential for providing food security, livelihoods, and income, especially in developing nations (WHO, 2018). The significance of riverine fisheries cannot be understated, as they support millions of people and contribute to the overall well-being of these communities with inland water reserves spanning 8,563,820 hectares (Jarwar, 2008). Over 59 million people are likely linked to fisheries and aquaculture in 2018 highlighting its importance for both cultural and economic well-being, especially in developing countries according to the Food and Agriculture Organization (FAO, 2020).
For the management and conservation of wild populations of L. rohita, it is important to understand the parameters of population dynamics of this fish species in its natural environment. Previously some studies were reported on the population dynamics of L. rohita from the Sylhet basin by Amin et al. (2001); from Dhir Beel by Goswami and Devaraj (1995); from Ganga and the Yamuna by Gupta and Tyagi (1992); in the Paisuni River by Dwivedi (2009); in the Rivers of Vindhyan region, India by Dwivedi and Nautiyal (2012); from Mymensingh Basin and Sylhet basin, Bangladesh by Haroon et al. (2001) and (2002). Although, earlier reported work describes the population dynamics of some fish species from Pakistani waters (Mohsin et al., 2016; Memon et al., 2017a, b, 2022), however, no research work has been carried out on the population dynamics of L. rohita. This study is the first attempt to provide information on the parameters of growth and stock status of L. rohita from the natural population of the Indus River. The study focuses on analyzing the growth and mortality characteristics of teleost bony fish in the Indus River, specifically the L. rohita species. To investigate the stock status various aspects such as growth parameters, mortality rates, biological reference points, growth performance indices, and virtual population analysis were examined. The research also aimed to determine the rate of exploitation and relative yield per recruit. The main goal and objective were to gain insights into the stock position and population parameters for the successful development and management of L. rohita in the Indus River. This study provides valuable information that was previously lacking, shedding light on important aspects of the fish population dynamics of L. rohita species in the region and will be useful for fisheries conservationists and environmentalists for the successful development, management, production and preservation in the Indus River.
Materials and Methods
Sampling
During the study period, the monthly samples of L. rohita were collected from the Indus River, at the site of Kotri Barrage (Ghulam Muhammad Barrage), Sindh, Pakistan (Fig. 1). A total of 720 fish specimens were used in the current study obtained from the fishermen’s catch at small-scale centres from January 2013 to December 2013. All individual samples were registered in the total length (cm) and total weight (g) with an average total length of 23±5.11cm (Mean±SD) and total weight at an average of 225±144.14g.
Analysis of data
The monthly length-frequency data of L. rohita was analyzed using the FISAT-II software (Gayanilo et al., 2005). Time-series data of size-frequency distributions at one 5cm intervals were obtained for each month (Table I). Following core population parameters such as growth, mortality rate, biological reference points, growth performance index, virtual population analysis and relative yield per recruit analysis were estimated in the present study.
Length-weight relationship
The lengths and weights of 720 specimens of L. rohita were determine according to Le Cren (1951). The parameters a and b of the length-weight relationship were estimated by the power equation: W= aLb, where the weight of fish was represented by W in grams (g), constant condition factor was represented by intercept (a), L was indicated by total length in (cm) and allometric growth parameter was represented by exponent or slope (b).
Table I. Length-frequency data of L. rohita from January 2013 to December 2013 in the Indus River, Pakistan.
|
Size classes |
Jan. |
Feb. |
Mar. |
Apr. |
May |
Aug. |
Sep. |
Oct. |
Nov. |
Dec. |
Total |
% |
|
15-19.9 |
36 |
54 |
65 |
20 |
5 |
2 |
0 |
0 |
0 |
0 |
182 |
25.28 |
|
20-24.9 |
16 |
44 |
64 |
54 |
56 |
26 |
1 |
0 |
0 |
0 |
261 |
36.25 |
|
25-29.9 |
0 |
0 |
0 |
0 |
37 |
53 |
41 |
28 |
2 |
9 |
170 |
23.61 |
|
30-34.9 |
0 |
0 |
0 |
0 |
0 |
6 |
20 |
10 |
30 |
41 |
107 |
14.86 |
|
Total |
52 |
98 |
129 |
74 |
98 |
87 |
62 |
38 |
32 |
50 |
720 |
100 |
Growth parameters
The von Bertalanffy growth function parameters of L. rohita were determined by using the method ELEFAN-I (Electronic Length Frequency Analysis) in this study, which makes direct use of size distributions to prepare an estimate of the growth parameters. The von Bertalanffy equation for growth in length according to Haddon (2011) is: Lt = L∞ (1–exp (-K (t– t0))), where Lt was the length at the predicted time t, L∞ was the asymptotic length, K was the growth coefficient and t0 was the hypothetical age or time where length was equal to zero. An additional estimated value of t0 was obtained by the empirical equation by Pauly (1983) as log10 (-t0) = -0.3922 – 0.275 log10L∞ - 1.038 log10K.
Mortalities rates
For the estimation of instantaneous total mortality (Z), the length-converted catch curve method by Pauly (1983) was used. Additional parameters of M and F (natural mortality and fishing mortality) were also calculated. The regression formula for Z is Ln (Nt) =Ln (N0) – Zt, where Nt is the population size at age t and N0 is the population size at 0 (Pauly, 1980). The equation by Pauly (1980) was used for natural mortality (M) from log10M= 0.0066 – 0.279 log10L∞ + 0.654 log10K + 0.4634 log10T. Where; T= 21oC was the average annual surface temperature of the water was analyzed with the help of digital thermometer in the Indus River in which the stock of L. rohita occurs. The F (Fishing mortality) was estimated by using the relationship of subtracting F = Z-M. The exploitation ratio (E) was obtained by the relationship of Gulland (1971a): E = F/Z = F/ (F+M).
Virtual population analysis
According to Sparre and Venema (1992), the length structured virtual population analysis (VPA) of L. rohita was carried out with the input values of length-weight relationship parameters intercept (a), slope (b) and growth parameters values of asymptotic length (L∞), growth coefficient (K) and mortality parameters values of natural mortality (M) and fishing mortality (F) to estimate the fishing mortalities per length class. The t0 value was taken as zero.
Biological reference points
According to Gulland (1969), the optimal fishing mortality rate Fopt= M was determined as the limit biological reference point for L. rohita in the Indus River.
Beverton and holt yield per recruit model
Using the model of Beverton and Holt (1957) incorporated into the FAO FiSAT-II program (Gayanilo et al., 2005) with the formula relative yield per recruitment (Y/R) values as a function of exploitation ratio (E) of L. rohita were estimated. where Yw/R was yield per recruit, tc was the average age of first capture, tr was the age of recruitment, tλ was the asymptotic ages, Ǫn was the constant and equal to 1, -3,3 and -1 when n was 0, 1, 2 and 3 correspondingly (Pitcher and Hart, 1982).
Growth performance indices
The estimated growth parameters values of L∞ (asymptotic length) and K (growth constant) were used to compute the growth performance index (Phi prime Φ’) following equations by Pauly and Munro (1984) Φ’= log10 K + 2log10L∞ and Φ= log10 K + 2/3 log10W∞ were used.
Results
Length-weight relationship
720 specimens of L. rohita were collected from the Indus River at Kotri Barrage during the period January 2013 to December 2013. The total length ranged between 15 and 35cm at an average length of 23 cm with SD±5.111cm, while total individual weight varied between 50 to 700g with an average of 225±144.14 (Mean±SD) g (Fig. 2). The length-weight relationship parameters a and b for L. rohita were described by the power equation as: W= 0.025 L2.844, R2= 0.990 (n=720). The maximum and minimum number of individual species was found at 20cm (n= 77) and while least was at 15cm (n= 5) respectively (Table I). Dominant length and weight of L. rohita were observed at ranges between 17 to 23cm (Fig. 3) and 65 to 150g, respectively.
Growth parameters
The procedure of K-scan was computed to estimate the L∞ (asymptotic length) and K (growth coefficient) through the method of ELEFAN-I. The monthly length frequency size distribution of L. rohita was arranged at 5cm intervals shown in Table I. The estimated values of L∞ and K were obtained as L∞= 36.75cm and K= 1.200 yr-1, respectively. The score of the goodness fit index of the ELEFAN-I routine (Rn= 0.313) was constructed by the total sum of observations in this function. Hypothetical age at zero length was estimated as t0= -0.904 years. The graphical representations of these output VBGF curves are shown in Figure 4.
Mortality and exploitation ratio
The value of instantaneous total mortality for L. rohita in Indus River Z= 2.06 yr-1 with CI95% of 1.65-2.46 (r2 = 0.895) was constructed from the input values of VBGF growth parameters (L∞ and K) in the length converted catch curve model described by Pauly (1983) (Fig. 5 and Table II). At the same time, the value of natural mortality was M= 1.662 yr-1 using Pauly’s (1980) equation. Fishing mortality (F= 0.398 yr-1) was obtained by subtracting Z from M and the exploitation ratio (E= 0.193) was achieved from the Gulland (1971a): E= F/Z= 0.398/ (0.398+1.662).
Table II. Estimated key parameters of growth, mortality, exploitation and yield of L. rohita from the Indus River in 2013.
|
Population parameters |
Labeo rohita from the River Indus |
|
Intercept (a) |
0.025 |
|
Exponent (b) |
2.844 |
|
Coefficient of determination (R2) |
0.99 |
|
Asymptotic length (L∞) |
36.75cm |
|
Growth coefficient (K) |
1.200 yr-1 |
|
Theoretical age (t) at zero length (t0) |
- 0.904 years |
|
Goodness of fit (Rn) |
0.313 |
|
Total mortality (Z) |
2.06 yr-1 at CI95% to 1.65 – 2.46 |
|
Mean annual water temperature of the Indus River |
21oC |
|
Natural mortality (M) |
1.662 yr-1 |
|
Fishing mortality (F) F= Z-M |
0.398 yr-1 |
|
Exploitation rate (E) E= F/Z |
0.193 |
|
GPI Φ' (L∞) |
3.210 |
|
GPI Φ (W∞) |
1.979 |
|
Length range (cm) |
15-35cm |
|
Sample number (n) |
720 |
Virtual population analysis
The input value of von Bertalanffy growth function of the growth parameters (L∞ and K), mortality parameters (M and F) and length-weight relationship parameters (a and b) were used to build the length structured virtual population analysis (LVPA) for the L. rohita in the Indus River. Cohort analysis to output graphics for LVPA was done by FiSAT-II (Fig. 6). The length of the high fishing mortality was observed in the 26.0 to 31.0cm range.
Biological reference points
The relative yield per recruitment for L. rohita was analyzed by the model of Beverton-Holt yield per recruit with the knife edge selection in FiSAT-II (Fig. 7). When tc was 1 the Fmax was estimated at 3 yr-1 and F0.1 to 2.1 yr-1. Since the current age at the first capture was approximately 1 year and Fcurrent was 0.398, the Fcurrent was smaller than Fmax and F0.1 indicating the stock of L. rohita in the Indus River is by the situation of the holding exploitation state. Biological reference point Fopt was equal to (M= 1.662). The current fishing mortality rate of 0.398 yr-1 was below the biological reference point target benchmark.
Growth performance index (GPI)
The von Bertalanffy growth parameters of L∞ and K were used for the estimation of growth performance indices (phi prime or index Φ’) for L. rohita in the Indus River as Φ’= 3.210 and Φ= 1.979.
Discussion
Freshwater fish in Pakistan are not only important for food security but also the livelihoods of those involved in commercial fishing, especially in inland waterlogged areas. However, studies in Pakistan have mainly focused on freshwater species diversity and composition, rather than key characteristics like fish population dynamics and conservation status of economically important freshwater fish species (Sheikh et al., 2017). The decline in the population of certain commercially significant freshwater fish species can be attributed to factors such as overexploitation, pollution, and habitat disintegration (Memon et al., 2017a). This highlights the need for further research and conservation efforts to protect these economically and commercially important species and sustain the livelihoods of fishing communities. The main purpose of fisheries stock assessment is to assist in fishery management (Gayanilo and Pauly, 1997). Length composition data is used to assess the current status of fish stocks. It is observed that fishing not only reduces the population of fish but also affects the relationships between different species (Sheikh et al., 2017). Analyzing the length frequency distribution of fish stocks is an important method for evaluating resources and managing fish populations that helps to prevent fragmentation within the fisheries sector (Maunder et al., 2016).
The study involved measuring the overall length of L. rohita specimens, ranging from 15.0 to 35.0 cm, and their weight, ranging from 50 to 700g. A total of 720 specimens were analyzed to study the length-weight relationship (LWR). The LWR parameters for L. rohita can be found in Table II. A high R2 value of 0.990 indicated a strong correlation between the length and weight of L. rohita. The exponent b value revealed a negative allometric growth pattern. In cases of isometric growth, the b value is 3, signifying that the fish maintains the same body shape throughout its life (Wootton, 1990; Pauly and Gayanilo, 1997). However, a b value greater or less than 3 indicates allometric growth, resulting in changes in the fish dimensions.
Table III. Comparison of estimated growth parameters of L. rohita in the Indus River with the other estimated growth parameters from the different countries.
|
Location |
L∞(cm) |
K (yr-1) |
t0 |
Φ' |
Reference |
|
Dhirbeel of Assam, India |
135.29 |
1.2 |
- |
- |
Goswami and Devaraj (1995) |
|
Sylhet basin, Bangladesh (1998) |
80.31 |
0.41 |
- |
- |
Haroon et al. (2002) |
|
Sylhet basin, Bangladesh (1999) |
51.74 |
0.8 |
- |
- |
|
|
Mymensingh basin, Bangladesh (1998) |
74.36 |
0.74 |
- |
- |
Harronet al. (2001) |
|
Mymensingh basin, Bangladesh (1999) |
97 |
0.7 |
- |
- |
|
|
Sylhet basin, Bangladesh |
80.2 |
0.41 |
- |
- |
Amin et al. (2001) |
|
Govindgarh Lake, India |
91.2 |
0.38 |
-0.13 |
3.5 |
Prakash and Gupta (1986) |
|
Aligarh Waters, India |
102 |
0.28 |
-0.33 |
3.46 |
Khan and Jhingran (1975) |
|
Paisuni river, India |
833 (mm) |
0.56 |
- |
- |
Dwivedi (2009) |
|
River Ken |
946 (mm) |
0.4 |
- |
- |
Dwivedi and Nautiyal (2012) |
|
River Paisuni |
833 (mm) |
0.56 |
- |
- |
|
|
River Tons |
962 (mm) |
0.42 |
- |
- |
|
|
Indus River, Pakistan |
36.75 |
1.2 |
-0.904 |
3.21 |
Present study |
Our study found a b value of 2.844 for L. rohita, demonstrating a negative allometric growth pattern. This aligns with the findings of Pauly and Gayanilo (1997), who suggested that b values typically range between 2.5 and 3.5.
This relationship helps in assessing the health and sustainability of fish stocks, which is vital for effective fisheries management. Overall, the LWR is a fundamental tool in fisheries science that aids in comprehending the biology and dynamics of fish populations. The fluctuations in the length-weight relationship (LWR) within the same species across different areas can be attributed to ecological and environmental conditions, habitat changes, or physiological factors (Le Cren, 1951). The provided text presents various studies documenting the b values for different fish species in different locations. Bhat (2011) found a b value of 2.97 for L. rohita fish in Phuj Reservoir, Jhansi, India. Choudhury et al. (1982) reported negative allometric growth (b= 2.347) in the Brahmaputra River, Assam, India. Khan and Jhingran (1975) reported b values of 2.533 in Panchet Reservoir, Damodar Valley, India, 2.698 in Tilaya Reservoir, Damodar Valley, India, and 2.808 in the Konar Reservoir, Damodar Valley, India. Garcia (2010) obtained a b value of 2.920 in Pampanga River, Candaba, Philippines. However, Khan and Jhingran (1975) observed a b value of 3.014 in the Ganges River, India. Ahmed and Saha (1996) reported a b value of 3.149 in Kaptai Lake, Bangladesh. Jhingran (1952) reported a b value of 3.0 in a moat and spring in Calcutta, India. Sarkar et al. (1999) observed b values of 3.306 and 3.125, respectively from Bundh and Hatchery-bred.
Understanding fish populations and effectively managing fisheries requires a thorough understanding of growth parameters (Quinn and Deriso, 1999). These parameters provide valuable insights into the growth rates, mortality rates, and recruitment patterns of fish populations (Hilborn and Walters, 1992; Hoggarth, 2006; Maunder et al., 2016). By analyzing these parameters, fisheries managers can make informed decisions to ensure sustainable fishing practices and conservation efforts (Hilborn and Walters, 1992; Hoggarth, 2006; Maunder et al., 2016). The study by Moreau et al. (1986) emphasizes that the estimated L∞ parameter of the von Bertalanffy growth function should closely correspond with the maximum length of the fish observed during the sample, with t0 being less than zero to ensure a positive length at zero age. In this study, the estimated asymptotic length L∞= 36.75 cm falls within the acceptable range of the total length of 35.00cm for L. rohita. The K and L∞ values for L. rohita are provided in Table II. The length-frequency data for L. rohita is displayed in a 5cm class interval (Table I) using the ELEFAN-I method, where the length range of 20.0-24.9cm accounted for over 36% (261 fishes) of the L. rohita fishery. The t0 value was determined as t0= -0.13 year for L. rohita in Govindgarh Lake, India by Prakash and Gupta (1986), while Khan and Jhingran (1975) discovered t0= -0.33 year for the same species in Aligarh waters, India (Table III). The t0 value acts as an indicator of growth rate in adults and adolescents, with negative values indicating a higher proportion of juveniles compared to the anticipated growth curve for adults, while positive t0 values suggest slower growth (King, 1997). Table III presents a comparison of the estimated growth parameters of L. rohita in the Indus River with those of other countries. In this particular study, the asymptotic length value for L. rohita was determined to be L∞= 36.75cm, which is lower than previous estimates. However, the growth coefficient value obtained, K= 1.200 yr-1, was found to be higher compared to findings from other regions. Hence, the current research conducted in the Indus River suggests that the growth of L. rohita may be superior to that observed in other studies.
The fish mortality parameter is a crucial parameter in fisheries population dynamics, accounting for the loss of fish within a fish stock due to death (Owen et al., 2023; Maunder et al., 2023). The natural mortality coefficient (M) is a critical factor in fisheries stock assessment but is also one of the least understood and most difficult to estimate due to unavailable direct data (Punt, 2023; Beverton and Holt, 1957; Gayanilo et al., 2005). The natural mortality coefficient (M) M is a key component in mathematical models used to study fish stock dynamics (Ping et al., 2018), with fishery scientists continuously striving to obtain precise estimates of M to enhance their understanding of fish populations and promote sustainable fisheries management practices for ensuring assessment outcomes accuracy and shaping fisheries management strategies (Maunder et al., 2023). Fishery scientists have been working to obtain reliable estimates of M to enhance their understanding of fish populations and establish a more scientific approach to fisheries management and sustainable development. This study focuses on one method for estimating the instantaneous rate of natural mortality in fish stocks and relies on the strong correlation between M with indirect methods of other life history parameters, such as maximum observed age, age at reproductive maturity, asymptotic fish length, and growth rate. The Pauly empirical equation (Pauly, 1980) is commonly used to assess L. rohita fisheries in Pakistan, playing a vital role in offering insights into fish population dynamics and guiding effective fisheries management practices.
The mortality rates and exploitation values of L. rohita were compared with those from other studies, as presented in Table IV. In this study, the total mortality (Z) was found to be slightly lower or higher than in previous studies. In this research, the calculation of the natural mortality (M) of L. rohita from the Indus River is determined using Pauly’s equation and was notably higher compared to reported values worldwide. Consequently, our estimated natural mortality rate indicates its reliability and validity. Additionally, the fishing mortality (F) rate was moderately lower in this study compared to others. Similarly, the exploitation ratio was also found to be the lowest in this study compared to values observed in other regions around the world. The M/K ratio, which is commonly observed for various fish species, has been documented to range from 1.12 to 2.50 (Beverton and Holt, 1957). Interestingly, our study reveals that the M/K ratio of 1.385 falls within this established range. The natural mortality rate is influenced by various factors, including old age, predation, environmental stress, and parasitic diseases (King, 1997). The exploitation ratio is a measure used to determine the extent of fishery utilization. The ideal level of utilization is achieved when the fishing mortality rate matches the natural mortality rate. The natural mortality rate is 1.662 yr-1, which is higher than the current estimated fishing mortality rate of 0.398 yr-1. Based on the research, the exploitation ratio is 0.193, indicating that the L. rohita stock is in a secure state. This meets the guideline set by Gulland (1971b) that the exploitation rate should not exceed 0.5.
Table IV. Comparison of estimated mortality parameters and exploitation rate of L. rohita in the Indus River with the other estimated mortality parameters and exploitation rate from the different countries.
|
Locality |
Z (yr-1) |
M (yr-1) |
F (yr-1) |
E |
Reference |
|
Sylhet basin, Bangladesh (1998) Sylhet basin, Bangladesh (1999) |
1.56 1.70 |
0.73 0.77 |
0.83 0.93 |
0.52 0.55 |
Haroon et al. (2002) |
|
Mymensingh basin, Bangladesh (1998) Mymensingh basin, Bangladesh (1999) |
3.09 2.64 |
1.12 0.99 |
1.97 1.65 |
0.64 0.62 |
Haroon et al. (2001) |
|
Sylhet basin, Bangladesh |
1.56 |
0.73 |
0.83 |
- |
Amin et al. (2001) |
|
Paisuni river, India |
3.67 |
0.94 |
2.73 |
- |
Dwivedi (2009) |
|
River Ken River Paisuni River Tons |
3.2 4.19 2.73 |
0.74 1.84 0.74 |
3.67 2.46 2.33 |
0.94 0.77 0.56 |
Dwivedi and Nautiyal (2012) |
|
Ganga River, Allahabad, India |
0.74 |
0.30 |
0.44 |
0.59 |
Gupta and Tyagi (1992) |
|
Indus River, Pakistan |
2.06 |
1.662 |
0.398 |
0.193 |
Present study |
The growth performance index (GPI) is determined by two VBGF parameters, K and L∞, as mentioned in Gatabu’s (1992) research. Phi prime (Φ’) is a specific parameter that indicates the lack of reliability in the estimated growth parameters of the same or related species within a particular stock, as described in Adedolapo’s (2007) study. The similarity of Φ’ with related species in different tropical regions serves as a measure of the calculated growth parameter’s reliability in the conducted study. GPI allows for the comparison of growth performance among fish species from different populations, whether they belong to the same or different environmental fish populations, as highlighted in Baijot and Moreau’s (1997) and Pauly and Munro’s (1984) studies. In this particular study, the GPI of the pooled data of L. rohita was determined to be 3.210, which aligns with some of the values obtained from different tropical fish. Prakash and Gupta (1986), reported a GPI of 3.50 for L. rohita from Govindgarh Lake, India, while Khan and Jhingran (1975) reported a GPI of 3.46 for L. rohita from Aligarh Waters, India. This index is also supported by the von Bertalanffy growth parameters (L∞ and K) as it facilitates the comparison of species growth, as stated in Pauly and Munro’s (1984) study. The growth rate (K) and asymptotic size (L∞) are influenced by multiple factors, making the comparison of growth rates a complex matter. Phi prime (Φ’) serves as a reliable indicator that effectively responds to these criteria and can help identify slight differences when compared to other indicators (Etim et al., 1999). The mean value of Φ’ for some significant fish species in Africa ranges from 2.65 to 3.32. Therefore, the Indus River fish L. rohita can be considered to have slow growth, as its Φ’ value of 3.210 was calculated to be lower. The lower growth performance of L. rohita in the Indus River may be due to genetic structure, overfishing, dietary patterns, and excess utilization.
Biological reference points are commonly used in the management and conservation of fisheries resources today (Haddon, 2011). These reference points, or BRPs, are defined as levels of fishing mortality and/or biomass. The two most well-known reference points are F0.1 and Fmax, which are widely used in fisheries management (Hilborn and Walters, 1992). Fmax is the target biological reference point and is considered as a function of fishing mortality (F) for a specific exploitation pattern against the maximum value of yield per recruit (Y/P). Fmax represents only the value of F that allows for the possible maximum yield per recruit from the cohort. On the other hand, F0.1 is another target reference point that is a function of the fishing mortality coefficient (F). When F=0, the yield per recruit is at its highest, and when F=Fmax, the yield per recruit decreases. F0.1 refers to the point at which F has a value that results in a 10% increase in yield per recruit when it is maximized (Hilborn and Walters, 1992). During our investigation, the biological reference point (BRP) was determined by Patterson (1992) as Fopt, which equals 0.5 M (0.831) and Flimit, which equals 2/3 M (1.108). These BRPs were lower than the criterion of Fopt=M set by Gulland (1969). The Beverton and Holt model with knife-edge selection in FiSAT-II to analyze the contour map of relative yield per recruit for L. rohita was used. The contour map (Fig. 7) showed that Fmax and F0.1 were estimated at 3 yr-1 and 2.1 yr-1, respectively, when tc was 1. Since the age of the first capture during the current study was approximately one year, the current fishing mortality rate (Fcurrent) of 0.398 yr-1 was lower than the baseline of biological reference points of Fmax and F0.1 indicating that the stock of L. rohita is stable in the downstream of Indus River.
Conclusion
Based on the current results of our study, it appears that the L. rohita species in Pakistan is in a safe state. The mortality rate of the species Fcurrent= 0.398 yr-1 is lower than the biological reference point Fopt= 1.662 yr-1 as determined by Gulland (1971). This suggests that the stock is stable in the Indus River. Our study has provided baseline information about the L. rohita fish and confirms the hypothesis that fishing pressure above current levels may endanger the stock of L. rohita in the Indus River.
Declarations
Acknowledgments
We would like to express our heartfelt gratitude to the fishermen of Kotri Barrage at the Indus River for their continued support throughout the data collection and to the Chairman Prof. Dr. Khalid Hussain Lashari, the Department of Fisheries and Aquatic Sciences for their eternal help in engaging to do research in the laboratory. I would like to express my appreciation to the Chinese Scholarship Council (CSC) for their sponsorship during my doctoral degree. We are also grateful to Dr Ali Muhammad Mastoi, Director General of Fisheries Sindh (Marine and Coastal Fisheries Development) Karachi, Mr Zulifqar Ali Larik, Director General of Fisheries Sindh (Inland) Karachi @ Hyderabad, Dr Muhammad Asim Kareem, Director of Fisheries Sindh (Marine) Karachi of Livestock and Fisheries Department, Government of Sindh, for their valuable care, support and best wishes.
Funding
This work is part of the Ocean University China’s Special Research Fund (201022001).
Ethical statement
All the individuals in this research work were handled carefully, we neither harmed nor damaged the animal. The study was conducted following the Declaration of the Ocean University of China, and the protocol was approved by the Ethics Committee of OUC (No. 201022001).
Statement of conflict of interest
The authors have declared no conflict of interest.
References
Adedolapo, A., 2007. Age and growth of the African Catfish, Schilbe mystus (Linnaeus, 1758) in Asejire and Oyan Lakes, South-Western Nigeria. J. Fish. Aquat. Sci., 2: 110-119. https://doi.org/10.3923/jfas.2007.110.119
Ahmed, K.K. and Saha, S.B., 1996. Length-weight relationships of major carp in Kapati Lake, Bangladesh. Naga ICLARM Q, pp. 19-22.
Ali, S.S., 1999. Freshwater fishery biology. Naseem Book Depot, Hyderabad, Sindh, Pakistan, pp. 1-330.
Amin, S.M.N., Haroon, A.K.Y. and Alam, M., 2001. A study on the population dynamics of Labeo rohita (Hamilton) in the Sylhet basin, Bangladesh. Indian J. Fish., 48: 291-296.
Ashraf, M. and Zafar, A., 2013. A survey of parasites of wild Rohu in Trimmu Headworks, Pakistan. World Aquacult., pp. 50-53. www.was.org
Baijot, E. and Moreau, J., 1997. Biology and demographic status of the main fish species in the reservoirs of Burkina Faso. In: Hydrological aspects of fisheries in small reservoirs in the Sahel region (eds. E. Baijot, J. Moreau and S. Bouda). Technical Centre for Agricultural and Rural Cooperation, Commission of the European Communities, Wageningen, Netherlands. pp. 79-109.
Beverton, R.J.H. and Holt, S.J., 1957. On the dynamics of exploited fish populations. Fishery Investigation Series II. Ministry of Agriculture, Fisheries and Food, London. pp. 553.
Bhat, J.A., 2011. Length-weight relationship and condition factor of Labeo rohita (Cyprinidae) in Phuj Reservoir, Jhansi, U.P., India. J. exp. Zool. India, 14: 339-344.
Bhatti, M.A., 1999. Water resource system of Pakistan. Status and issues. Pakistan Science Foundation, Islamabad, ISBN. 969- 8040-14-5, 72.
Chondar, S.L., 1999. Biology of finfish and shellfish. SCSC Publisher,, Howrah, pp. 514.
Choudhury, M., Kolekar, V. and Chandra, R., 1982. Length-weight relationship and relative condition factor of four Indian major carps of river Brahmaputra, Assam. J. Int. Fish. Soc. India, 14: 42-48.
Dwivedi, A.C., 2009. Ecological assessment of fishes and population dynamics of Labeo rohita (Hamilton), Tor tor (Hamilton) and Labeo calbasu (Hamilton) in the Paisuni River. Aquaculture, 10: 249-259.
Dwivedi, A.C. and Nautiyal, P., 2012. Stock assessment of fish species Labeo rohita, Tor tor and Labeo calbasu in the rivers of Vindhyan region, India. J. environ. Biol., 33: 261-264.
Eschmeyer, W.N. and Fong, J.D., 2016. Species by family/subfamily in the catalogue of fishes. Institute for Biodiversity of Science and Sustainability, California Academy of Sciences.
Etim, L., Lebo, P.E. and King, R.P., 1999. The dynamics of an exploited population of a siluroid catfish (Schilbe intermidius Reupell 1832) in the Cross River, Nigeria. Fish. Res., 40: 295-307. https://doi.org/10.1016/S0165-7836(98)00217-3
FAO, 2009. Fishery and aquaculture country profile. FAO’s Fisheries Department, Rome. pp. 1-18.
FAO, 2011. Fisheries and aquaculture technical paper, No. 557. FAO, Rome.
FAO, 2020. The state of world fisheries and aquaculture. https://www.fao.org/state-of-fisheries-aquaculture/2020/en/
Frimodt, C., 1995. Multilingual illustrated guide to the world’s commercial warm-water fish. Fishing News Books, Osney Mead, Oxford, 215.
Garcia, L.M.B., 2010. Species composition and length-weight relationship of fishes in the Candaba wetland on Luzon Island, Philippines. J. appl. Ichthyol., 26: 946-948. https://doi.org/10.1111/j.1439-0426.2010.01516.x
Gatabu, A., 1992. Growth parameters and total mortality in Oreochromis niloticus (Linnaeus) from Nyanza Gulf, Lake Victoria. Hydrobiologia, 232: 91-97. https://doi.org/10.1007/BF00014617
Gayanilo, F.C. and Pauly, D., 1997. FAO ICLARM stock assessment tools (FISAT). References Manual. FAO Computerized Information Series (Fisheries), No 8, 262.
Gayanilo, F.C., Sparre, P. and Pauly, D., 2005. The FAO-ICLARM stock assessment tool (FiSAT) user’s guide. FAO computerized information series (Fisheries), FAO, Rome: World Fish Center, No 7: 168.
Goswami, P.K. and Devaraj, M., 1995. Instantaneous mortality estimates of rohu (Labeo rohita) in the Dhir beel ecosystem of the Brahmaputra basin, Assam, India. J. Int. Fish. Soc. India, 27: 1-5.
Gulland, J.A., 1969. Manual of methods for fish stock assessment part 1. Fish population analysis. Fishery Resources and Exploitation Division, FAO, Rome: pp. 154.
Gulland, J.A., 1971a. Estimation of mortality rates. Annex to Artic Fisheries working group report. ICES C.M. Doc. 3 (mimeo).
Gulland, J.A., 1971b. The fish resources of the oceans: West by fleet survey. Fishing News (Books) limited, for FAO, pp. 255.
Gupta, R.A. and Tyagi, K.R., 1992. Analytical approach to the analysis of the fish stock of the Ganga River system. J. Int. Fish. Soc. India, 24: 20-27.
Haddon, M., 2011. Modelling and quantitative methods in fisheries. Chapman and Hall/ CRC Press, London, pp. 449. https://doi.org/10.1201/9781439894170
Hamilton, B., 1822. Fishes of the Ganges. Archibald Constable and Company, Edinburgh, pp. 301-388.
Haroon, A.K.Y., Alam, M., Amin, S.M.N., Dewan, S. and Islam, S., 2002. Population dynamics of gangetic major carp from the Sylhet basin, Bangladesh. Indian J. Fish., 49: 161-168.
Haroon, A.K.Y., Razzaque, M.A., Dewan, S., Amin, S.M.N. and Rahman, S.L., 2001. Population dynamics and stock assessment of Labeo rohita (Ham.), L. calbasu (Ham.) and L. gonius (Ham.) from the Mymensingh basin, Bangladesh. J. biol. Sci., 1: 671-675. https://doi.org/10.3923/jbs.2001.671.675
Hilborn, R. and Walters, C.J., 1992. Quantitative fisheries stock assessment: choice, dynamics and uncertainty. Kluwer Academic Publishers, Boston/Dordrecht/London. https://doi.org/10.1007/978-1-4615-3598-0
Hoggarth, D.D., 2006. Stock assessment for fishery management: A framework guide to the stock assessment tools of the fisheries management and science programme. FAO Fisheries Technical Paper. No. 487. Food and Agriculture Organization, Rome.
Indus River, 2012. (Online). In: Berkshire encyclopedia of sustainability: Afro Eurasia: Assessing sustainability (ed. R. Anderson). Berkshire Publishing group Great Barrington, MA. Available from: http://search.credoreference.com/content/entry/berksae/indus_river/0 [Accessed 22 June 2016].
Jarwar, A.A., 2008. Status overview of fisheries and aquaculture development in Pakistan with context to other Asian countries. Aqua. Asia., 13: 13-18.
Jhingran, V.G., 1952. General length-weight relationship of three major carps of India. Proc. natl. Inst. Sci. India, 18: 449-460.
Kahlown, M.A. and Majeed, A., 2003. Water resources situation in Pakistan: Challenges and future strategies. COMSATS’ Series of Publication on Science and Technology: Water Resources in the South: Present Scenario and Future Prospects, Islamabad, Pakistan, pp. 221.
Khan, H.A. and Jhingran, V.G., 1975. Synopsis of biological data on rohu Labeo rohita (Hamilton, 1822). FAO Fish. Synop., 111: 100.
King, R.P., 1997. Growth performance of Nigerian fish stocks. Naga ICLARM Quart., 20: 31-35.
Le Cren, E.D., 1951. The length-weight relationship and seasonal cycle in gonad weight and condition in the perch (Perca fluviaittlis). J. Anim. Ecol., 20: 201-219. https://doi.org/10.2307/1540
Maunder, M.N., Crone, P.R., Punt, A.E., Valero, J.L. and Semmens, B.X., 2016. Growth: Theory, estimation, and application in fishery stock assessment models. Fish. Res., 180: 1–3. https://doi.org/10.1016/j.fishres.2016.03.005
Maunder, M.N., Hamel, O.S., Lee, H.H., Piner, K.R., Cope, J.M., Punt, A.E., Ianelli, J.N., Castillo-Jordan, C., Kapur, M. and Methot, R.D., 2023. Review of estimation methods for natural mortality and their performance. Fish. Res., 257: 106489. https://doi.org/10.1016/j.fishres.2022.106489
Memon, A.M., Liu., Q., Baloch, W.A., Soomro, A.N., Mohsin., M., Noman, M. and Karim, E., 2017a. Population parameters of siluroid catfish (Eutropiichthys vacha) from Indus River, Pakistan. Int. J. Agric. Biol., 19: 751-760. https://doi.org/10.17957/IJAB/15.0352
Memon, A.M., Liu, Q., Baloch, W.A., Mohsin, M., Karim, E., Liao, B., Jatoi, S., Han, Y. and Zhang, Q., 2017b. Growth parameters and mortality rates of giant river-catfish Sperata seenghala from the Indus River, Pakistan. Ind. J. Geo-Mar. Sci., 46: 1462-1469.
Memon, K.H., Memon, A.M., Ursani, T.J., Shaikh, A.M. and Memon, S.W., 2022. Population Parameters and Exploitation Status of Clown Knifefish Notopterus chitala (Hamliton, 1822) from Indus River, Pakistan. Pakistan J. Zool., 54: 889-899. https://doi.org/10.17582/journal.pjz/20200615120649
Mirza, M.R., 1975. Freshwater fishes and zoogeography of Pakistan. Bijdragen tot de Dierknnde, 45: 143-180. https://doi.org/10.1163/26660644-04502001
Mirza, M.R., 2003. Checklist of freshwater fishes of Pakistan. Pakistan J. Zool., (Suppl. Ser. No. 3): 1-30.
Mohsin, M., Mu, Y.T., Hussain, K., Mahmood, A., Sun, Z.Q., Nazir, K. and Wang, W., 2015. Contribution of fish production and trade to the economy of Pakistan. Int. J. mar. Sci., 5: 1-7. https://doi.org/10.5376/ijms.2015.05.0018
Mohsin, M., Mu, Y.T., Memon, A.M., Kalhoro, M.T. and Shah, S.B.H., 2016. Fishery stock assessment of Kiddi shrimp (Parapenaeopsis stylifera) in the Northern Arabian sea coast of Pakistan by using surplus production models. Chinese J. Ocean. Limn. https://doi.org/10.1007/s00343-017-6096-3
Moreau, J., Bambino, C. and Pauly, D., 1986. A comparison of four indices of overall growth performance based on 100 tilapia populations (Fam. Cichlidae). In: The first Asian fisheries forum (eds. J. Maclean, L.B. Dizon and L.V. Hosillo). Asian Fish. Soc. Manila, pp. 201-206.
Mushtaqur, R., 1975. A geography of Sindh Province, Pakistan. The Karachi Geographers Association. Karachi, Oxford University Press, pp. 93-96.
Owen, S.H., James N.I., Maunder, M.N. and Punt, A.E., 2023. Natural mortality: Theory, estimation and application in fishery stock assessment models, Fish. Res., 261: 106638. https://doi.org/10.1016/j.fishres.2023.106638
Pakistan Economic Survey, 2019-20. Economic adviser’s wing: Finance Division, Islamabad, Government of Pakistan. pp. 17-40 Available from: 02-Agriculture-02-06-2020 (finance.gov.pk).
Patterson, K., 1992. Fisheries for small pelagic species: An empirical approach to management targets. Rev. Fish Biol. Fish., 2: 321-338. https://doi.org/10.1007/BF00043521
Pauly, D., 1983. Some simple methods for the assessment of tropical fish stocks. Fish. Tech. Pap., 234: 52. FAO, Rome, Italy.
Pauly, D., 1980. On the interrelationships between natural mortality, growth parameters and mean environment temperature in 175 fish stocks. J. Cons. Cons. Perman. Int. Expl. Mer., 39: 175-192. https://doi.org/10.1093/icesjms/39.2.175
Pauly, D. and Gayanilo, Jr. F.C., 1997. A bee: An alternative approach to estimating the parameters of a length-weight relationship from length frequency samples and their bulk weight. Research report Naga, ICLARM, Manila, Philippines waters. Fish. Res., 21: 465-469.
Pauly, D. and Munro, J.I., 1984. Once more on the comparison of growth in fish and invertebrates. FishByte, 2: 21-23.
Peter, T., 1999. Coldwater fish and fisheries in Pakistan: FAO, Rome. Fish. Tech. Pap., 385: 122-137.
Ping G., Zhang, K., Xu, S. and Chen, Z., 2018. Assessment of natural mortality coefficients in fish stocks: A review. J. Fish. Sci. China, 25: 694-704. https://doi.org/10.3724/SP.J.1118.2018.17399
Pitcher, T.J. and Hart, P.J., 1982. Fisheries ecology. Chapman and Hall, London, pp. 414.
Prakash, S. and Gupta, R.G., 1986. Studies on the comparative growth rates of three major carps of the Govindgarh Lake. Indian J. Fish., 33: 45-53.
Psomadakis, P.N., Osmany, H.B. and Moazzam, M., 2015. Field identification guide to the living marine resources of Pakistan. FAO species identification guide for fishery purposes. The Food and Agriculture Organization of the United Nations, Rome, Italy and Marine Fisheries Department, Ministry of Ports and Shipping, Government of Pakistan, pp. 1-486.
Punt, A.E., 2023. Those who fail to learn from history are condemned to repeat it: A perspective on current stock assessment good practices and the consequences of not following them. Fish. Res., 261: 106642. https://doi.org/10.1016/j.fishres.2023.106642
Quinn, T.J. and Deriso, R.B., 1999. Quantitative fish dynamics. Oxford University Press, New York/Oxford. https://doi.org/10.1093/oso/9780195076318.001.0001
Rafique, M., 2007. Biosystematics and distribution of the freshwater fishes of Pakistan with special references to the subfamilies Noemacheilinae and Schizothoracinae. Ph.D. dissertation, UAAR, pp. 220.
Riede, K., 2004. Global register of migratory species from global to regional scales. Final Report of the R and D-Project 80805081. Federal Agency for Nature Conservation, Bonn, pp. 329.
Sarkar, S.K., Medda, C., Ganguly, S. and Basu, T.K., 1999. Length-weight relationship and relative condition of Bundh and Hatchery-bred Labeo rohita (Ham.) during the early period of development. Asian Fish. Sci., 12: 289-296. https://doi.org/10.33997/j.afs.1999.12.3.009
Sheikh, M., Laghari, M.Y., Lashari, P.K., Khooharo, A.R. and Narejo, N.T., 2017. Current status of three major carps (Labeo rohita, Cirrhinus mrigala and Catla catla) In the Downstream Indus River, Sindh. Fish Aqua. J., 8: 222. https://doi.org/10.4172/2150-3508.1000222
Sparre, P. and Venema, S.C., 1992. Introduction to tropical fish stock assessment. Part-1 Manual FAO, Fish. Tech. Pap., 306: 376.
Talwar, P.K. and Jhingran, A.G., 1991. Inland fisheries of India and adjacent countries. Oxford and IBH Publishing Co. New Delhi, pp. 541.
WHO, 2018. The state of food security and nutrition in the world 2018. Building climate resilience for food security and nutrition. Food and Agriculture Organization of the United States of America.
Wootton, R.J., 1990. Ecology of teleost fishes. Chapman and Hall, London. https://doi.org/10.1007/978-94-009-0829-1
Wootton, R.J., 1998. Ecology of teleost fishes. 2nd ed.: Kluwer, Dordrecht.
Yu, W., Yang, Y.C., Savitsky, A., Alford, D., Brown, C., Wescoat, J., Debowicz, D. and Robinson, S., 2013. The Indus Basin of Pakistan: The impacts of climate risks on water and agriculture. World Bank. Washington D.C. pp. 165. https://doi.org/10.1596/978-0-8213-9874-6