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Fish Diversity and Water Quality in Different Zones of Upper River Indus Basin, Pakistan

PJZ_54_6_2791-2799

Fish Diversity and Water Quality in Different Zones of Upper River Indus Basin, Pakistan

Zaidi Zona, Zulfiqar Ali*, Rida Ahmad and Irfan Zainab

Environmental Health and Wildlife Laboratory, Institute of Zoology, University of the Punjab, Lahore, Pakistan

ABSTRACT

Water quality assessment and freshwater fish diversity of cold-water Indus River, along a 400-kilometer stretch from Raikot (upstream) to Tarbela (downstream) was examined during 2019. The river channel was divided into five zones such as Raikot-Basha, Basha-Dasu, Dasu-Pattan, Pattan-Thakot and Thakot-Tarbela. The mean water quality of study site was as follows: pH 7.32, air temperature 21.15°C, water temperature 15.9°C, dissolved oxygen (DO) 6.41 mg/L, Total Dissolved Solids (TDS) 125.62 mg/L total hardness 77.50 mg/L, alkalinity 72.17 mg/L (as CaCO3) and conductivity 129.04 µs/cm. Planktonic study revealed the presence of variety of phytoplankton (n=31) and zooplankton (n=3) species in study area. In total, 37 fish species were found in the study area, with species richness rising from zone one (n =10) to zone five (n =33). Altogether, the fish diversity represents 25 genera and 13 families. To analyze the data, principal component analysis (PCA) was done by using XLSTAT and excel 2019 to study the factors affecting the water quality. The eigenvalues obtained after PCA from zone 1 to zone 5 were 5.40, 2.40, 1.90, 0.28 and <0.28, respectively. The higher eigenvalue of zone 1 suggests large dispersion of data in this region. Furthermore, the findings in the study indicate that warm water, higher conductivity, DO, high nitrate concentration, and high salinity manifested to be the best habitat conditions downstream of Thakot area. To conserve the richness and integrity of fish communities, it is recommended that instream flow evaluations to include target species that occupy flow-sensitive habitat categories.


Article Information

Received 18 October 2021

Revised 23 December 2021

Accepted 11 January 2022

Available online 04 February 2022

(early access)

Published 25 August 2022

Authors’ Contribution

ZZ and ZA conceptualized the study. ZZ, RA and IZ collected the data from field. ZZ, ZA and RA analyzed the data and drafted the manuscript. ZA supervised the research.

Key words

Fish diversity, River Indus, Water quality, Conductivity, Salinity

DOI: https://dx.doi.org/10.17582/journal.pjz/20211018201037

* Corresponding author: zali.zool@pu.edu.pk

0030-9923/2022/0006-2791 $ 9.00/0

Copyright 2022 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

Freshwater ecosystem is home to many threatened species. Therefore, it is essential to understand the factors responsible for affecting these taxa and subsequently causing reduction in the species population size (Dudgeon et al., 2006). One of the challenges to these species is low nutrient load and water pollution, which can have both chronic and acute effects on aquatic animals (Dixit, 2015; Boyd, 2010; Hossain et al., 2019).

The use of biological indicators to study the quality of freshwater ecosystems is a common strategy (Joy and Death, 2004). Among these biological indicators, fish is the most sensitive and valuable indicator of water quality change (Raja et al., 2015; Nazeer et al., 2016). Moreover, fish diversity evaluation, as well as the investigation of their connection, might be a low-cost yet effective water quality assessment method (Qadir and Malik, 2009). Also, Planktons are consumed by all freshwater fish species at some point in their lives, and their variety and abundance may be related to fish diversity (Mummert and Drenner, 1986). Additionally, Planktons also serve a significant function in aquatic ecosystems; They not only turn plant material into animal food, but they are also a vital component of fish food and may be used to assess the health of waterbodies (Verma and Munshi, 1987).

Indus River is Pakistan’s largest river with total length of 3,180km while the area of basin is 1,165,000 km2. The river originates from Tibetan Plateau, running from south, it discharges in Arabian Sea (Sobkowiak et al., 2020). More than 180 fish species have been found in Pakistan belonging to different classes, orders, families and genera including exotic, endemic and native species. On the basis of International Union of Conservation of Nature (IUCN) status, indigenousness, socioeconomic importance, out of these, 86 species (i.e., 8 exotic and 78 native) have been labeled as the species of special importance (Din et al., 2016). The fish diversity of lower Indus Basin was studied by Hussain (1973), while Ahmad et al. (1976) published the check list containing Indus River’s ichthyofauna. According to Abro et al. (2020), nine studies have been conducted on fish fauna from various parts of Indus River including (Urooj et al., 2011; Mirza et al., 2014; Saeed et al., 2013; Muhammad et al., 2017; Navid et al., 2017; Sheikh et al., 2017). However, the relationship between fish diversity, nutrient load and heavy metal concentration are not too well studied in this particular area.

Based on the significance of the area in question, the Indus River Basin, and fresh water ecosystems, it is critical to analyse the factors involving water quality, nutrients, sediment load, and fish variety in the Indus River Basin. The primary goal of this study was to better understand the variation in water quality and fish diversity in the Indus cold-water environment.

MATERIALS AND METHODS

Study area

The study area for current research extended from Raikot Bridge to Tarbela Reservoir (Fig. 1). The area was divided into five zones, such as Raikot to Basha (zone 1), Basha to Dasu (zone 2), Dasu to Pattan (zone 3), Pattan to Thakot (zone 4) and Thakot to Tarbela (zone 5).

Thirty tributaries were chosen from around fifty on the left and right bank of the Indus River (six for each zone), and one sample was obtained from tributary and one from the Indus River (10m downstream of selected tributaries). The study took place over the course of four seasons in 2019. In each season, ten days were spent in the study area. Physico-chemical and biological data were acquired during the field survey for this investigation. In addition to that, water samples were also collected to determine the nutrient load and the levels of heavy metals.

 

Physico-chemical parameters

Water pH, temperature, Dissolved Oxygen (DO), water depth, color, hardness, sediments, Carbon dioxide (CO2), Nitrate (NO3), conductivity and alkalinity were determined with the help of Quick Analysis Kit. Environmental kit was used to determine the titration values of CO2, alkalinity, hardness, nitrate and other nutrient content. Temperature was measured by digital thermometer while pH of water was measured by digital pH meter (HANNA HI 8314 Membrane pH Meter).

Fish sampling

Local fishermen were hired to collect the fish samples. Gillnets were used to capture fish from main river stream and other tributaries coming from left and right bank. Moreover, Formalin solution (5-10%) was used to preserve the fish samples immediately after capturing for identification purpose. Furthermore, weight and length of fish samples were also recorded.

Phytoplankton and zooplanktons

In the same way, plankton nets with different mesh sizes such as 40mm, 60mm and 80mm were utilized for plankton collection. In order to catch the macrophytes, stones were also turned up and down. Both floating and submerged vegetation were also collected for identification.

Principal component analysis (PCA)

PCA is a linear combination of different factors which is applied to normalize factors for the purpose of comparison. It is further used to find the factors of pollutants affecting the sample and ultimately offers certain explanation for the most valuable component. XLSTAT (14-day trial) and Excel 2019 were used for various analyses in this manuscript.

RESULTS

The current study was carried out to investigate the fish diversity and water quality including nutrient load, heavy metals along with other physiochemical parameters in a 400km stretch of Indus River from Raikot Bridge to Tarbela Reservoir.

The study area was found to be home to a total of 37 species (Table I), including native (27), exotic/introduced (6), and endemic (4) species. Cypriniformes was the most abundant order in the study area with 21 species, followed by Siluriformes with seven species. The fact was also established that the species richness increased from upstream to downstream. Species richness was maximum (33) in Thakot to Tarbela. There were five species that were found exclusively in this region including Nile Tilapia (Oreochromis niloticus), silver hatchet chela (Chela cachius), two spot barb (Puntius ticto), stocki Catfish (Glyptothorax stocki), striped gourami (Colisa fasciata). The species richness from zone one to zone four was 10, 13, 18 and 29, respectively.

 

Table I. Fish diversity of study area.

Order/ family

Species (Common name)

Zones (fish presence)

Occurrence

1

2

3

4

5

Cichliformes

Cichlidae

1. Oreochromis niloticus (Nile Tilapia)

-

-

-

-

+

Introduced

Cyprinidae

2. Barilius pakistanicus (Barila)

-

+

+

+

+

Native

3. B. vagra (Gheur, Korang)

+

+

+

+

+

Native

4.Catla catla (Thaila)

-

-

-

+

+

Native

5. Cirrhinus mrigala (Mrigal carp)

-

-

-

+

+

Native

6. Cyprinus carpio (Common carp)

-

-

-

+

+

Introduced

7. Gara gotyla (Sucker head)

+

+

+

+

+

Native

8. Hypophthalmichthys molitrix (Silver carp)

-

-

+

+

+

Introduced

9. H. nobilis (Bighead carp)

-

-

+

+

+

Endemic

10. Labeo caeruleus (blue rohu)

-

-

-

+

+

Introduced

11. L. rohita (Rohu)

-

-

-

+

+

Native

12. Puntius sophore (Pool barb)

-

-

-

+

+

Introduced

13. P. terio (Onespot barb)

-

-

+

+

+

Native

14. Schizothorax esocinus (Chirruh snow trout)

+

+

+

+

+

Native

15. S. labiatus (Kunar snow trout)

+

+

+

+

-

Native

16. S. plagiostomus (Snow trout)

+

+

+

+

-

Native 

17. Tor macrolepis (Indus mahseer)

-

-

+

+

+

Native

18. T. putitora (Golden mahseer)

-

-

-

+

+

Native

Nemacheilidae

19. Triplophysa hazaraensis (Hazara loach)

-

+

+

+

+

Endemic

Perciformes

Channidae

20. Channa gachua (Dwarf snakehead)

-

-

-

+

+

Native

Cichliformes

Cichlidae

21. Oreochromis mossambicus (Mozambique Tilapia)

-

+

+

+

+

Introduced

Siluriformes

Schilbeidae

22. Clupisoma garua (Chel-lee )

+

+

+

+

+

Native

23. C. naziri (Naziri Bachcha)

+

+

+

+

+

Native

Bagridae

24. Mystus bleekeri (Bleeker's Mystus)

-

-

+

+

+

Native

25. Rita rita (Bengal catfish)

-

-

+

+

+

Native

26. Sperata sarwari (Singhara)

+

+

+

-

-

Native

27. S. seenghala (Tengara)

+

+

-

-

-

Native

Siluridae

28. Wallago attu (Helicopter catfish)

-

-

-

+

+

Native

Sisoridae

29. Glyptothorax punjabensis (Punjab catfish)

+

+

+

+

+

Endemic

30. Glyptosternum reticulum (Turkestan catfish)

-

-

-

-

+

Native

Synbranchiformes

Mastacembelidae

31. Mastacembelus armatus (Spiny eel)

-

-

-

+

+

Native

Cypriniformes

Cyprinidae

32. Chela cachius (Silver hatchet chela)

-

-

-

-

+

Native

33. Puntius ticto (Two spot barb)

-

-

-

-

+

Native

Botiidae

34. Botia birdi (Indian loaches)

-

-

-

-

+

Native

Siluriformes

Sisoridae

35. Glyptothorax stocki (Stocki catfish)

-

-

-

-

+

Endemic

Anabantiformes

Osphronemidae

36. Colisa fasciata (Striped gourami)

-

-

-

-

+

Native

Osteoglossiformes

Notopteridae

37. Notopterus notopterus (Bronze featherback)

-

-

-

-

+

Native

 

In the current investigation, the maximum mean value of pH (7.34) was recorded in the area between Pattan to Thakot. The mean of DO ranged from 6.0± 2.21 (Dasu to Pattan) to 7.2±3.73 mg/L (Thakot to Tarbela). Naturally, with an increasing tendency in electrical conductivity, the region between Thakot to Tarbela has the highest value (181.89 ± 22.59 s/cm) and the lowest (98± 8.40 s/cm). From Basha to Dasu, the salinity reached a maximum mean of 105± 9.15mg/L. The average of turbidity was likewise at its highest in the Basha to Dasu region, reaching 14.24± 3.67 NTU, while lowest from Dasu to Pattan with mean concentration 3.552±1.29 NTU. Similarly, the maximum concentration of ammonia was found in this zone, with a mean value of 0.900± 0.38 mg/L. In the same way, it is essential to measure total dissolved solids (TDS) in order to assess water quality. TDS increased in value as the same moved from upstream (Raikot) to downstream (Tarbela), reaching a maximum of 146.86±3.41 mg/L. Furthermore, the highest concentrations of carbon dioxide and iron were found in the Raikot to Basha region, with 17.03±1.51 and 2.168±8.27 mg/L of carbon dioxide and iron, respectively. Nitrate concentrations increased from zone one to zone five, with the highest concentration (24.11±6.18 mg/L) occurring in the Thakot to Tarbela region and the lowest concentration (7.68±3.54 mg/L) occurring in the Raikot to Basha region (Table II). Figure 2 shows that almost all water quality parameters had an increasing trend from zone 1 to zone 5.

Principal component analysis

According to PCA, the factor loadings (FL) can be explained and classified into strong, moderate and weak. If FL is more than 0.75 then it is classified as strong while if FL is between 0.75 and 0.50 then it is moderate. FL is classified as weak if it is between 0.50 and 0.30 (Shaw, 2009). The factor loadings for studied water quality parameters are presented in Table III.

The variance corresponding to PCA-1 was 54.04% with strong positive loadings (>0.8) by electrical conductivity, salinity, total dissolved solids (TDS), total hardness, alkalinity and lead. Furthermore, moderate negative loading of TDS and strong negative loading of iron in PCA-2 suggested their negative correlation with the pollution sources. In all PCs, the positive loading of lead and negative loadings of pH are common.

Figure 3 displays the quality parameters in two PCAs and reveals that PCA-1 has strong negative loading on pH, DO, turbidity and lead, moderate loading on total hardness, total alkalinity, and salinity while strong positive loadings on TDS and conductivity.

 

Table II. Physico-chemical parameters (Mean±SD) of different zones study area.

Parameters

Raikot to Basha

Basha to Dasu

Dasu to Pattan

Pattan to Thakot

Thakot to Tarbela

River Indus

Temperature (°C)

14.30±7.65

14.04±7.29

15.33±8.47

16.70±9.16

19.56±10.44

15.99±2.25

pH

7.28±2.95

7.28±3.12

7.39±1.17

7.34±1.81

7.31±2.66

7.32±0.04

Electrical conductivity (µs/cm)

98.81±8.40

111.02±2.15

117.97±4.35

135.50±6.52

181.89±22.59

129.04±32.39

Salinity (mg/L)

77.08±7.58

86.02±9.45

63.02±4.72

82.46±5.20

105.72±9.15

82.86±15.49

T.D.S (mg/L)

140.34±6.45

106.45±7.51

100.18±6.70

134.25±7.49

146.86±3.41

125.61±20.95

Turbidity (NTU)

4.71±1.09

14.24±3.67

3.55±1.29

7.12±.49

9.01±3.98

7.73±4.21

Total. Hardness (mg/L)

76.20±5.82

60.53±2.11

62.42±3.58

92.21±4.03

96.13±5.41

77.50±16.43

Total Alkalinity (mg/L)

68.39±7.60

62.05±2.99

58.17±2.50

79.86±3.13

92.33±8.78

72.16±13.94

Ammonia (mg/L)

0.50±0.13

0.68±0.28

0.63±0.27

0.61±0.24

0.90±0.38

0.66±0.14

Carbon dioxide (mg/L)

17.03±1.51

12.04±8.18

10.02±4.24

9.20±3.03

14.69±6.84

12.60±3.25

Phosphate (mg/L

15.52±1.54

16.47±1.15

13.87±3.93

13.52±13.90

14.26±3.68

14.73±1.23

Nitrate (mg/L)

7.68±3.54

8.32±4.15

8.76±5.57

12.77±11.56

24.11±6.18

12.33±6.87

Iron (mg/L)

2.16±8.27

0.85±0.96

0.63±0.44

0.68±0.60

0.52±0.26

0.97±0.67

Lead (mg/L)

0.03±0.03

0.04±0.04

0.05±0.05

0.04±0.05

0.06±0.05

0.04±0.01

DO

6.63±3.13

5.56±0.53

6.00±2.21

6.64±1.42

7.21±3.73

6.41±0.63

NO2

0.01±0.13

0.01±0.04

0.14±0.27

0.11±0.74

0.30±0.17

0.11±0.11

Air Temp (oC)

13.21±2.48

17.14±3.71

21.47±3.97

24.81±13.52

29.14±17.63

21.15±6.25

Seechi disc. (cm)

75.74±9.00

74.55±6.42

67.00±4.72

64.84±8.39

44.45±9.37

65.31±12.57

 

Note: Bold figure is the maximum mean value.

 

 

Table III. Factor loadings of water quality parameters.

PCA-1

PCA-2

PCA-3

pH

-0.161

-0.589

-0.410

Conductivity (µs/cm)

0.911

0.369

0.166

Salinity (mg/L)

0.843

-0.232

0.475

T.D.S (mg/L)

0.811

-0.596

-0.310

Turbidity (NTU)

0.089

-0.220

0.967

Total Hardness (mg/L)

0.927

-0.094

-0.238

Total Alkalinity (mg/L)

0.992

-0.074

-0.006

DO (mg/L)

-0.884

-0.125

-0.447

Iron (mg/L)

-0.305

-0.816

-0.442

Lead(mg/L)

0.676

0.658

0.051

Eigenvalue

5.405

2.405

1.908

Variability (%)

54.048

24.053

19.078

Cumulative %

54.048

78.100

97.179

 

The eigenvalues obtained after PCA from zone 1 to zone 5 were 5.40, 2.40, 1.90, 0.28 and <0.28, respectively. The higher eigenvalue of zone 1 suggests large dispersion of data in this region. Bipolar plot for water quality parameters in Figure 4 indicates that Zone 5 has strong positive loading with PC-1 and is a least polluted zones having only lead as a notable pollutant while zone 1 had strong negative loading having lead with both PC-1 and PC-2.

 

 

Overall, thirty-four types of planktons including 31 types of phytoplankton and three types of zooplankton were recorded from Raikot to Tarbela. These phytoplankton belonged to Chlorophyta (12 genera), Bacillariophyta (12 genera), Cyanophyta (4 genera), Euglenophyta (2 genera) and Cryptophyta (one genus). Similarly, among zooplankton, Rotifer (2 genera) and Protozoans (1 genus) were recorded. Out of 34, there were 31 types of planktons found in Raikot to Basha zone which were followed by 27 types in Basha to Dasu region. Furthermore, Pattan to Thakot region had the lowest number planktons (19) while the number increased to 29 in Thakot to Tarbela region (Table IV).

Furthermore, total five species of macroinvertebrates were recorded in the study area including: Caddisfly larvae, Chironomus, mosquito larvae, Lymnaea sp. and Valvata sp. These five types were present in the region Thakot to Tarbela (Table V) while only first three types were found in other aforementioned four zones of the study area.

DISCUSSION

During the current research, an increasing trend was observed in species richness from upstream to downstream and the results acquired were in agreement with (Solbe and Cooper, 1975). Maximum, (33) species were observed in Thakot to Tarbela region. According to Mirza et al. (2011), downstream from Thakot to Tarbela the fish diversity increases. Elevated conductivity makes this region a better habitat for fish fauna (de Carvalho, 2017) because species prefer habitat that fulfil their specific requirements (Vieira and Tejerina-Garro, 2020). Moreover, the fish diversity was highest at intermediate salinity and high nitrate concentration (Thakot to Tarbela) which indicates that the fish fauna in this region is tolerant to deteriorating water quality (Duque et al., 2020).

Indus Mahseer is a game fish found from Dasu to Tarbela. IUCN has declared Mahseer as endangered (Jha et al., 2018). Furthermore, Peter (1999) reported that due to overfishing it is becoming very rare and it might disappear due to submergence of its spawning ground. Similar observation was made in the current study as only a few specimens of Mahseer were found in the study area. In addition to that, various developmental projects are planned in the study area including Thakot hydropower project (WAPDA, 2021) which may cause an increase its vulnerability. Schizothorax was abundant in study area and according to Khan et al. (2018), this species in widely distributed in Indus River and also a major food source for the residents and the results were in accordance to the current study. Furthermore, Ali et al. (1980) and Peter (1999) also observed Twospot Barb, Indian Loaches, Striped Gourami, Stocki Catfish and Bronze featherback in and near Tarbela. Among exotic fishes, Turkestan catfish and common carp were also recorded by Akhtar (1991) in the current study area. Gebilion catla, silver carp, common carp, mori, Hazara loach Schizothorax and Mahseer were also reported by Rafique and Khan (2012) in the study area.

 

Table IV. Phytoplankton and zooplankton of study area.

Plankton

Raikot to Basha

Basha to Dasu

Dasu to Pattan

Pattan to Thakot

Thakot to Tarbela

Phytoplankton

Cyanophyta

Microcyctis

+

+

+

+

+

Merismopedia

+

+

-

-

+

Nostoc

+

+

-

-

+

Rivularia

-

+

+

-

+

Chlorophyta

Oedogonium

+

+

+

+

+

Coelastrium

+

+

-

-

-

Chlaymydomonas

+

+

+

+

+

Volvox

+

+

+

+

+

Closterium

+

-

+

-

+

Tetraedron

-

+

-

-

+

Dictyosphaerium

+

+

+

+

+

Ankistrodesmus

+

+

+

-

-

Pyramimonas

-

+

-

-

+

Chaetophora

+

-

-

-

+

Chrysophyta

Synura

+

-

-

+

-

Bacillariophyta

Diatom

+

+

+

+

+

Navicula

+

+

+

+

+

Pleurosigma

-

-

-

-

-

Fragillaria

+

-

-

-

+

Cymbella

+

+

+

+

+

Achnanthes

+

+

+

+

+

Cynedra

+

+

-

+

+

Ghomphonema

+

-

-

+

+

Hannea

+

+

+

-

+

Rhoicosphenia

+

+

-

+

+

Cyclotella

+

-

+

+

+

Achnanthedium

+

+

+

-

+

Craticula

+

-

-

-

-

Cryptophyta

Rhodomonas

+

+

+

+

+

Euglenophyta

Euglena

+

+

+

+

+

Trachelomonas

+

+

-

-

-

Zooplanktons

Rotifer

+

+

+

+

+

Moina

+

+

+

-

+

Daphnia

+

+

+

+

+

Protozoans

Paramecium

+

+

+

+

+

 

Table V. Macroinvertebrates in different zones of study area.

Macroinvertebrates

Raikot to Basha

Basha to Dasu

Dasu to Pattan

Pattan to Thakot

Thakot to Tarbela

Caddisfly larvae

186

154

73

86

62

Chironomus

626

414

144

103

105

Mosquito larvae

246

121

21

27

124

Lymnaea species

0

0

0

0

9

Valvata species

0

0

0

0

14

 

Water quality, pH, temperature, DO and conductivity directly impact the species richness (Oberdorff et al., 2001). The oxygen consumption during fermentation at higher rate results in production of organic acid and ammonia that can lead to decreased pH. The negative loading of pH and strong positive loading of lead show in in Table III are also in accordance with this argument. Similar findings were reported by Baluch and Hashmi (2019) in upper Indus Basin.

In the present study, maximum mean value of pH (7.34) was in the zone of Dasu to Pattan. The DO values of each zone were within the DO limits recommended by United Nations Economic Commission of Europe (UNECE) for freshwater quality to maintain the aquatic life (UNECE, 1994). The electrical conductivity had an increasing trend with maximum mean value (181.89 ± 22.59s/cm) value in the region of Thakot to Tarbela. Conductivity, TDS, total hardness, total alkalinity, nitrate, DO and species richness had increasing trend from upstream to downstream and similar conclusions were made by Solbe and Cooper (1975) during the research on freshwater fisheries of River Churnet. Additionally, turbidity and electrical conductivity play a significant role in species diversity and different species prefer variable habitats due to variation in their ecological requirements (Huang et al., 2019). Total alkalinity, TDS, DO and hardness in the region of Pattan to Thakot were 92.33±8.78, 146.86±3.41, 7.21±3.73 and 96.133±5.41 mg/L, respectively, in the current research but according to the study conducted by Usman et al. (2019) the five-year maximum mean values for these parameters were recorded as 175, 179, 7.6 and 145 mg/L, respectively. With reference to planktons, the following Chlorophyta and Bacillariophyta were the most abundant and the results were in accordance with the study conducted by Ali et al. (2003).

Figure 3 showing the quality parameters in two PCs reveals that PCA-1 has strong negative loading on pH, DO, Lead and Turbidity, moderate loading on total hardness, total alkalinity, and salinity while strong positive loadings on TDS and conductivity. The results revealed that PCA-1 is affected by organic as well as inorganic pollution due to soil erosion The strong negative loading of PCA-1 with pH and DO is consistent with the results in published literature (Baluch and Hashmi, 2019). Furthermore, negative loadings of DO suggests the presence of organic acid and the results are in consistence with previous research (Chounlamany et al., 2017). Results further confirms that the major source of pollution in study area are either heavy metals such as lead or other anthropogenic pollution sources (Baluch and Hashmi, 2019).

Understanding spatial fish assemblages in relation to their water quality is critical for fish assemblage management and conservation. The findings of this study will aid future efforts to forecast the effects of hydropower projects on the aquatic fish assemblages of the River Indus. In the future, it will be critical to regulate the massive untreated domestic and industrial loads to surface water prior to discharge, as well as to enforce rules and regulations and impose severe penalties on offenders.

Statement of conflict of interest

The authors have declared no conflict of interest.

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