Water quality assessment in relation to fish assemblage using multivariate analysis in Manasbal Lake, Kashmir

ABSTRACT

Water is necessary for the survival of any living being on this planet and in today’s world, it has become a limiting resource because of anthropogenic pressures like pollution, climate change, overexploitation etc. To maintain the water bodies in a proper condition from time to time, analysis of the water quality is highly recommended. So an attempt was made to have a detailed analysis of the surface water quality of the deepest freshwater lake in India, the Manasbal Lake, and to know the impact of these parameters on the distribution of fish fauna in the lake. The different physicochemical aspects of the lake were analyzed spatially and seasonally for a period of two years. The results from the principal component analysis revealed that the main parameters affecting the water quality in Manasbal Lake include total dissolved solids, electrical conductivity, total phosphorus, nitrates, pH, free carbon dioxide, dissolved oxygen and alkalinity. The study also reported a similarity in physicochemical aspects as well as the type of fish fauna from Sites-I and Site-III. Overall the physicochemical aspects were seen to impact the distribution of different fish species in the lake as reported from the canonical correspondence and cluster analysis. pH and nitrates were found to impact the distribution of fish species like Cyprinus carpio, Carassius carassius, Schizothorax niger and S. curvifrons whereas the main parameters affecting the distribution of Pethia conchonius, Crossocheilus diplochilus and Gambusia holbrooki were dissolved oxygen, free carbon dioxide and water temperature. The overall water quality of the lake is good for the proper growth and survival of the fish species and also for domestic purposes. This study will be very helpful to form baseline information for future research, as very scanty information is available related to such work.

KEYWORDS:

• Canonical correspondence analysis
• habitat preferences
• physicochemical parameters
• principal component analysis
• freshwater

Introduction

Water, a worthful and precious gift of nature, is a basic necessity for the sustenance of life on earth (Chidambaram, 2010) forming the main element without which, no life can be imagined. It is a vital and indispensable component in the growth and development of any kind of life throughout the globe (Reddy, Balakrishna, & Reddy, 2015). The role of water is found in the day-to-day activities of huge economic sectors like industries, electricity generation, agricultural growth and development, and above all, fisheries sector (Tyagi, Sharma, Singh, & Dobhal, 2013). Even though water covers almost ¾^th of the earth, but only 2 to 3% exists as freshwater and amongst that merely 5% is available for carrying out all necessary life functions, with the rest being locked up in glaciers (Chidambaram, 2010; Sandeep, Vinit, Madhullica, & Anshu, 2011).

Fish assemblage in a water body is an important part of hydrobiology, taking into consideration all the biotic and abiotic factors affecting them, including physicochemical aspects of the water body, flow regime, temperature changes, pollution stress, habitat destruction, and over-exploitation (Karaouzas, Theodoropoulos, Vardakas, Kalogianni, & Th Skoulikidis, 2018; Revenga, Campbell, Abell, De Villiers, & Bryer, 2005; Schlosser, 1982). The physicochemical parameters of a water body are thus vital in determining the diversity of aquatic fauna, especially fish diversity, and both physicochemical as well as biological components of a water body act as the indicators of the health of the water body (Moyle, 1993). This makes assessment of the water quality and the biotic elements of a water body quite an important aspect for the proper management of both the resources.

Rivers and lakes serve a variety of essential purposes, including the generation of electricity, irrigation, fisheries, and supplying drinking water. World-wide environmental concerns impacting water bodies, include the eutrophication of rivers and lakes due to surplus nutrient input and the contamination of surface water with hazardous substances (Filik Iscen et al., 2008). Aquatic ecosystems are thought to receive a significant amount of toxins and nutrients from urban, industrial, and agricultural activity, with their excess leading to a variety of issues, including toxic algal blooms, oxygen depletion, fish mortality, biodiversity loss, disappearance of aquatic plant beds, and the destruction of coral reefs (Ouyang, Nkedi-Kizza, Wu, Shinde, & Huang, 2006). A balanced ecological community can exist when there is positive interaction between the environment and the living organisms (Ntengwe, 2006). Physical, chemical, and biological factors are used to evaluate the quality of water. A balanced ecological community cannot exist in contaminated surface waters. An ecosystem is balanced when there is positive interaction between the environment and the living organisms inside it (Ntengwe, 2006; Rocha, Andrade, & Lopes, 2015). Since maintaining a healthy environment depends on the quality of the water, this link is undoubtedly important, and monitoring the latter becomes mandatory.

The famous valley of Kashmir, surrounded by lofty Himalayas and the Pir-Panjal mountain ranges is bestowed with breathtaking scenic beauty. The Kashmir Valley is geographically and climatically an ideal place for nature lovers due to the abundance of lush green pastures, fast-flowing streams, attractive lakes and springs, ever-green fields, and dense forests which enhance its grandeur and are a source of great attraction for tourists. The valley is known all over the world for its water resources in the form of freshwater lakes, streams, and rivers. The one’s worth mentioning include the Wular Lake, Dal Lake, Manasbal Lake, Kounsarnag Lake, Neelnag Lake, the River Jhelum with its fast-flowing tributaries like the Vishav stream, Lidder nallah, Sindh nallah etc. and famous springs like Verinag, Kokernag, Cheshmashashi, and Achabal. These water bodies not only add to the beauty of the valley but also form a means of livelihood for a vast community of people (Raina, 2002). A varied assortment of freshwater bodies may be found in Kashmir valley, with lakes playing a particularly significant ecological function (Gul et al., 2021). The lakes of Kashmir are located in the flood basin of the Jhelum River, where its wide meanders have cut marshy lowlands out of the Karewas terraces. These lakes are classified as glacier, alpine, or valley lakes based on their origin, altitudinal location, and biota, and they give a good opportunity for investigating the structural and functional processes of an aquatic biological system (Zutshi, Kaul, & Vass, 1972). The present work aimed to analyze the impact of water quality on distribution of the inhabiting fish fauna of the deepest freshwater lake in India, the Manasbal Lake, keeping in view its economic importance for the people living in the surroundings of the lake and the increasing pollution load and deterioration process of the water bodies throughout the globe.

Materials and methods

Study area

The famous Manasbal Lake is situated about 30 km to the north of Srinagar city in the Ganderbal district of Kashmir Valley. The lake lies between the geographical coordinates of 34°14ˈ- 34°15ˈ North and 74°39ˈ- 74°41ˈ East at an altitude of 1584 m.a.s.l (Naik, Rashid, & Balkhi, 2015; Shafi, Kamili, Shah, Bandh, & Dar, 2017). Manasbal Lake is known to be the deepest freshwater lake of India with a depth of about 12 m (Lawrence, 1895; Qadri et al., 2021; Shafi, Kamili, & Shah, 2012; Yousuf, Bakhtiyar, Andrabi, & Wani, 2023). The lake is surrounded by three villages on its embankments viz; Kondabal, Jarokbal and Gratbal and also by mountain ranges of moderate height having limestone deposits. This lake is of semi-drainage nature having only a permanent outlet source called the Nunnyar Nallah through which it drains into the river Jhelum and water in the Manasbal Lake has its source in the springs (approximately 1200) present at its bottom (Andrabi, Parveen, & Bakhtiyar, 2021; Jamila et al., 2014). The lake is famous for its enchanting bloom of Nelumbo nucifera (lotus) during the autumn season and is a paradise for bird lovers as a large population of migratory birds use this lake as their stamping ground, thus is rightly tilted as the “Supreme gem of all Kashmir Valley lakes” (Shafi et al., 2012; Zutshi & Vass, 1977). The climatic condition in and around the lake is similar to that of rest of the Kashmir valley, with the average annual precipitation being approximately 823.9 mm, while the average annual maximum and minimum temperatures being 19.6 °C and 6.8 °C, respectively. In recent years, the valley has seen a rise in yearly precipitation and relative humidity due to change in climate (Parvaze, Ahmad, Parvaze, & Kanth, 2017).

For the conduct of curent study the entire lake was divided into three different study sites according to the variability in surrounding areas and the type of water quality, pollution level, and aquatic vegetation.

Site I: This site is at the main entrance of the lake deemed as a famous tourist attraction. A lot of human activities in the form of fish cleaning and selling the catch, tourists and visitors polluting through plastic remains of eatables, shikara and boat riders etc, are seen at this site.

Site II: This site lies at the open water central zone and includes the deepest part of the lake with clear water and less visible macrophytic growth and pollution load.

Site III: It is situated on the northern bank of the lake having direct human interference from the inhabitant village, in the form of disposal of domestic wastes, sewage and agricultural wastes into the lake. The pollution level here is evident from the growth of macrophytic vegetation at this site.

Sampling procedure

In order to assess the physicochemical parameters of the Manasbal Lake, water samples were obtained from the surface level on a monthly basis for a period of two years (March-2018 to February-2020) at three sampling stations viz, Site-I (main entrance point), Site-II (center of the lake) and Site-III (with human habitation on the bank) (Figures 1 and 2). Sampling for both fish and water samples was done during the morning hours from 9 am to 12 pm. During the present study 12 physicochemical parameters were studied using standard methodologies including water temperature (WT) by mercury thermometer, dissolved oxygen (DO) using Winkler’s Iodometric method (APHA, 2017), pH, electrical conductivity (EC) and total dissolved solids (TDS) were measured using multiparameter meter (HANNA H19829). The water samples for parameters like free carbon dioxide (FCO₂), total alkalinity (Alk), chloride (Cl⁻), total hardness (TH), total phosphorus (TP), nitrate-nitrogen (NO₃-N) and nitrite-nitrogen (NO₂-N) were taken in acid-washed sampling bottles (1000 mL) and analyzed using standard methodologies (APHA, 2017) at the Fish Biology and Limnology Research Laboratory, Department of Zoology, University of Kashmir. Testing of water samples was done in triplicates and finally the mean of the triplicates was taken into consideration.

Figure 1. Map of Manasbal Lake showing the sampling sites.

Figure 2. Study sites of the Manasbal Lake.

Fish catch assessment was carried out monthly on the sampling days with the help of expert fishermen using nets of varied mesh sizes viz, cast net (1.3 to 3.0 cm), gill net (4.5 to 7.5 mm) and hand net. The fishes were identified with the help of taxonomic keys given by Talwar and Jhingran (1991) and Kullander, Fang, Delling, and Ahlander (1999). The sorting and counting of the fishes was done on spot.

Statistical analysis

The analysis of water quality parameters was carried out by descriptive statistics using one-way ANOVA and Duncan’s multiple range test (p < 0.05), taking into consideration the mean values of the data on seasonal and spatial basis. Also to know the significant relation among different physicochemical aspects linear regression analysis was carried out.

Multivariate statistical tools, including principal component analysis (PCA) and cluster analysis (CA) were applied to the data to see the variability of different components and their impact on the overall water quality of the lake. Principal component analysis (PCA) seeks to discover a condensed set of features that capture the essence of the initial data in a lower-dimensional space, minimizing the loss of information (Kherif & Latypova, 2020), utilizing a smaller number of independent variables to explain the variation of a large dataset of associated variables (Simeonov et al., 2003). It yields eigenvalues based on the covariance of the original variables and determines the results in the form of loadings and allows for data reduction with the least amount of original information loss (Hair, Anderson, Tatham, & Black, 1995; Sharma, 1996; Vega, Pardo, Barrado, & Debán, 1998). For cluster analysis, hierarchical agglomerative clustering (HAC) was used based on Ward’s methods as it often uses a dendrogram to demonstrate and give a visual representation of the similarities between each sample and the complete data set (Nidheesh, Nazeer, & Ameer, 2020; Shrestha & Kazama, 2007; Tabachnick & Fidell, 1996).

To know the impact of the physicochemical parameters on the distribution of fish assemblages in Manasbal Lake different statistical tools were used viz; Pearson’s correlation, canonical correspondence analysis (CCA), cluster analysis (CA), and non-metric multidimensional scaling (NMDS). Pearson’s correlation was used to determine the significant positive and negative relation between different water quality parameters and the fish fauna of the lake. Canonical correspondence analysis (CCA) is the best tool to explain the variation in species distribution and abundance with respect to environmental variables (Mensah et al., 2018). For the present study, 7 fish species and 12 environmental variables were used to obtain the ordinations which revealed the impact of water quality on the distribution of respective fish species. CA and NMDS were plotted to see the distribution of the fish fauna with respect to the sites chosen for the study.

For statistical analysis software like MS Excel-2016, PAST ver. 4.03 and SPSS ver. 20 were used.

Results and discussion

The pattern of physicochemical parameters and their spatial and seasonal variation

The overall trend followed by the different physicochemical parameters of Manasbal Lake is given in Table 1 and during the analysis measures like mean, standard deviation, minimum and maximum of 12 physicochemical parameters were analyzed. Also spatial and seasonal variation in these physicochemical aspects was assessed using one-way ANOVA (Tables 2 and 3) to know the significant and non-significant variations in the different parameters. Graphical representation in the form of box plots showing spatial variation in physicochemical aspects is given in Figure 3.

Figure 3. Box plots showing the spatial variation in different physicochemical parameters of Manasbal Lake.

Table 1. Overall trend shown by the physicochemical parameters of Manasbal Lake.

Parameters	Minimum	Maximum	Mean ± SD
Water Temperature (^oC)	5.5	25.7	15.6 ± 6.08
Dissolved Oxygen (mg/L)	4	15.6	8.60 ± 2.26
pH	7.5	8.5	8.04 ± 0.25
Free carbon dioxide (mg/L)	2.2	7	3.9 ± 0.92
Alkalinity (mg/L)	96	190	130.8 ± 21.88
Chloride (mg/L)	8	21.02	14.3 ± 3.26
Total Hardness (mg/L)	94.5	278	190.4 ± 46.27
Electrical Conductivity (µs/cm)	150	400	282.8 ± 62.77
Total Dissolved Solids (mg/L)	97	200	148.0 ± 29.34
Total Phosphorus (µg/L)	75	235	136.1 ± 43.15
Nitrates (µg/L)	85.6	230	128.0 ± 37.34
Nitrites (µg/L)	6.2	45.6	20.8 ± 9.47

Table 2. Spatial variation in physicochemical aspects of Manasbal Lake.

Parameters	Site-I	Site-II	Site-III
Water Temperature (^oC)	15.6 ± 6.00^a	15.6 ± 6.50^a	15.5 ± 6.21^a
Dissolved Oxygen (mg/L)	8.8 ± 1.77^a	9.1 ± 1.28^a	8.9 ± 2.58^a
pH	8.0 ± 0.21^a	8.1 ± 0.23^a	8.1 ± 0.29^a
Free carbon dioxide (mg/L)	4.1 ± 0.57^a	3.7 ± 0.86^a	3.7 ± 1.09^a
Alkalinity (mg/L)	136.7 ± 21.11^a	130.0 ± 21.63^a	125.6 ± 22.35^a
Chloride (mg/L)	13.1 ± 2.77^b	14.4 ± 3.80^ab	15.4 ± 2.84^a
Total Hardness (mg/L)	175.7 ± 46.70^b	192.0 ± 44.61^ab	203.6 ± 45.08^a
Electrical Conductivity (µs/cm)	282.5 ± 71.67^a	297.8 ± 57.34^a	286.2 ± 60.96^a
Total Dissolved Solids (mg/L)	149.1 ± 31.81^a	144.6 ± 28.57^a	150.1 ± 28.46^a
Total Phosphorus (µg/L)	134.0 ± 39.81^a	132.6 ± 44.57^a	141.6 ± 46.13^a
Nitrates (µg/L)	122.6 ± 35.80^a	136.4 ± 38.50^a	125.1 ± 37.80^a
Nitrites (µg/L)	18.1 ± 8.01^a	22.6 ± 9.18^a	21.6 ± 10.82^a

The values sharing same superscripts in a row are not statistically significant (p > 0.05)

Table 3. Seasonal variation in physicochemical parameters of Manasbal Lake.

Parameters	Spring	Summer	Autumn	Winter
Water Temperature (^oC)	16.3 ± 4.05^b	22.9 ± 1.37^a	14.6 ± 4.43^b	8.7 ± 2.61^c
Dissolved Oxygen (mg/L)	9.5 ± 1.49^a	7.2 ± 1.71^b	8.4 ± 2.26^ab	9.6 ± 2.46^a
pH	8.0 ± 0.30^a	8.0 ± 0.27^a	8.1 ± 0.27^a	8.0 ± 0.13^a
Free carbon dioxide (mg/L)	3.9 ± 0.75^ab	3.4 ± 0.63^b	3.9 ± 0.74^ab	4.0 ± 0.89^a
Alkalinity (mg/L)	135.2 ± 16.15^a	122.6 ± 25.59^a	131.6 ± 16.61^a	136.0 ± 17.28^a
Chloride (mg/L)	16.5 ± 2.09^a	13.9 ± 3.01^bc	14.5 ± 3.59^b	12.2 ± 2.82^c
Total Hardness (mg/L)	158.2 ± 26.53^c	235.6 ± 21.95^a	157.8 ± 47.60^c	210.3 ± 26.15^b
Electrical Conductivity (µs/cm)	308.4 ± 20.31^b	339.8 ± 27.83^a	234.2 ± 37.25^c	227.7 ± 33.45^c
Total Dissolved Solids (mg/L)	143.4 ± 18.68^b	181 ± 13.67^c	151.1 ± 21.67^b	116.3 ± 18.46^a
Total Phosphorus (µg/L)	131.2 ± 29.88^b	177.3 ± 42.38^b	129 ± 46.21^b	106.8 ± 12.91^a
Nitrates (µg/L)	113.7 ± 7.53^b	183.8 ± 27.94^a	101.5 ± 14.58^b	112.9 ± 16.60^b
Nitrites (µg/L)	13.3 ± 4.21^b	24.6 ± 12.64^a	22.8 ± 6.81^a	16.4 ± 5.10^b

The values sharing same superscripts in a row are not statistically significant (p > 0.05)

Temperature is an important parameter influencing the physical, chemical and biological aspects of a lake. It directly influences the rate of carbon dioxide utilization in photosynthesis by phytoplankton as well as has a pronounced effect on biological activity, rate of decomposition, nutrient recycling and also impacts the rate of dissolution of different gases in the water (Gulzar & Abubakr, 2019; Toufeek & Korium, 2009). In present study, the water temperature showed significant variation with respect to seasons (p < 0.05) and was found to be maximum during summer season (22.9 ± 1.37 °C) pertaining to high air temperature and more solar radiation being received by the lake water during summer resulting in increased water temperature. The minimum temperature was reported during winter season (8.7 ± 2.61 °C) due to low air temperature as air temperature and water temperature are closely related to each other (Wanganeo, 1980; Yogesh & Pendse, 2001). On the spatial basis water temperature did not show much variation owing to small size of the lake and also even distribution of solar radiation during every season. Similar results were reported by Ngaira (2006), Toufeek and Korium (2009), Dar, Mir, Bhat, and Bhat (2013), Omondi et al. (2014), Reddy et al. (2015) and Gudoo, Gupta, and Mir (2018) in their respective water bodies.

Dissolved oxygen (DO) forms an important parameter indicating the health of an aquatic ecosystem. Its proper concentration is necessary to carry out different biochemical as well as metabolic activities in the living organisms (Mishra & Yadav, 1978; Yang, Shen, Zhang, & Wang, 2007). During present study the overall mean value of DO was reported to be 8.60 ± 2.26 mg/L with maximum concentration reported during the winter season (9.6 ± 2.46 mg/L) and minimum during summer (7.2 ± 1.71 mg/L). Low concentration of DO during the summer season may be due to increased biological activity with increase in temperature and more consumption of DO (Arafat, Bakhtiyar, Mir, & Islam, 2022; Korium & Toufeek, 2008). Site II was reported to have the maximum DO (9.1 ± 1.28 mg/L) which might be due to more photosynthetic activity of macrophytes as well as more surface area available for dissolution of oxygen gas and also low sewage and nutrient disposal at this site. Kumar, Mandal, and Kumar (2004), Ganie, Khan, and Parveen (2012) and Tabassum, Tiwari, and Mir (2018) provided similar insights on the seasonal fluctuation in DO levels. Tabassum et al. (2018) reported a dissolved oxygen range of 6.9 to 8.9 mg/L, with a maximum value recorded during winter and a minimum value recorded during summer from Manasbal Lake.

Hydrogen ion concentration is an important chemical property of water which explains the influence of different biotic and abiotic ecological aspects of an aquatic ecosystem. It is the indicator of the acid-base equilibrium of a water body which is influenced and maintained by dissolution of different compounds into the water body (Gulzar & Abubakr, 2019; Naik et al., 2015). Klein (1962) reported the ideal range of pH to be from 7.2 to 8.7 for the survival of aquatic organisms. During our study the range of pH was reported to be 8.04 ± 0.25 showing not much variation in different seasons and also at the respective sites. This range of pH is ideal for the sustenance of different biotic organisms in the said lake. The results yielded from our study are in agreement with those of Naik et al. (2015) and Gudoo et al. (2018), both reporting alkaline water from Manasbal Lake.

Carbon dioxide is an important component of photosynthesis and in an aquatic ecosystem it is added from different sources like decomposition, respiration and also with its reaction with water to form an unstable compound called carbonic acid which readily decomposes into carbonates and bicarbonates responsible for variation in pH of water body and also retainment of equilibrium concentration of CO₂ in a water body (Chandler, 1970; Naik et al., 2015; Wetzel, 2001). During the present study a significant variation (p < 0.05) was reported in the concentration of FCO₂ on the seasonal basis and high concentration of FCO₂ was reported during the winter season (4.0 ± 0.89 mg/L) and lowest during the summer season (3.4 ± 0.63 mg/L) which can be directly related to its inverse relation with water temperature as with increase in temperature dissolution of gases decrease. Also during winter there is increased decomposition activity as well in the lower layers adding to the concentration of FCO₂. Further on the spatial grounds Site I was reported to have highest concentration of FCO₂ due to low water level and presence of large number of small forage fish species like Gambusia holbrooki and Pethia conchonius which tend to live in schools in the littoral areas. Also there is increased pollution load at this site due to human interference as well. Our results are in conformity to earlier workers including, Coole (1979), Sakhare and Joshi (2002), Ahangar, Saksena, Mir, and Ahangar (2012). Ahangar et al. (2012) also reported higher values of carbon dioxide in the autumn and winter season from Anchar Lake.

Alkalinity is a rough indicator of the ability to neutralize the acidic components in a water body. The alkalinity of water is mostly due to the presence of carbonates and bicarbonates of calcium and magnesium and hydroxide ions formed during the dissolution of CO₂ in the water (Balkhi, Yousuf, & Qadri, 1987). Moyle (1945) characterized lakes on the basis of alkalinity into three types viz. lakes with alkalinity range upto 40 mg/L were grouped as soft lakes, alkalinity range of 40–90 mg/L as medium and lakes with alkalinity range above 90 mg/L were designated as hard water lakes. During our study alkalinity was reported to be above 90 mg/L in all the seasons and at all the sites which means the Manasbal Lake is a hard water type lake. The maximum alkalinity was reported during the winter season (136.0 ± 17.28 mg/L) and minimum during the summer (122.6 ± 25.59 mg/L) which is due to the fact that during winter as a result of low temperature there may be accumulation of more bicarbonate ions due to their less uptake by phytoplanktons. Also the diurnal changes in rate of photosynthesis cause changes in alkalinity. Further, high alkalinity at Site I can be due to low water level along with direct disposal of sewage water and more human interference. Our findings get support from works of Khan, Jadhav, and Ustad (2012), Bhat, Meraj, Yaseen, Bhat, and Pandit (2013), Naik et al. (2015) and Tabassum et al. (2018).

The amount of chloride in water is a good indicator of pollution due to organic matter which is mostly of animal source (Kumar et al., 2004; Venkatasubramani & Meenambal, 2007). It is also added from the decomposition as well as runoff from the nearby mountain rocks and minerals (Ramesh & Jagadeeswari, 2012). In the present study the range of Cl⁻ was reported to be 14.3 ± 3.26 mg/L. On seasonal basis a significant difference in Cl⁻ concentrations was seen (p < 0.05) with high concentration of Cl⁻ during the spring season (16.5 ± 2.09 mg/L) and lowest during the winter season (12.2 ± 2.82 mg/L) owing to the fact that during spring more frequent rains lead to addition of runoff water from surrounding mountain ranges along with the sewage water and also with increase in common household activities lead to addition of more organic nutrients. It is also noticed that during winter season due to low temperature there is very less human interference and less nutrients as well. On spatial basis Site III was found to have high concentration of Cl⁻ due to the sewage runoff as well as impact of direct household activities of the inhabitants of the nearby village. Similar observations have been reported by Kumar et al. (2004), Dar et al. (2013) and Hassan, Arnold, and Mishra (2018).

Hardness of water is mainly due to the presence of alkaline earth metal ions in the form of calcium, magnesium and other multivalent cations like carbonates, bicarbonates, sulfates, chlorides and other household sources like soaps, detergents etc. (Gudoo et al., 2018; Rahman, Bashar, Farhana, & Hossain, 2014). Water quality association has put forth the criteria of nature of water body on the basis of hardness as, if the range of hardness is from 0 to 17 mg/L water is regarded to be soft, if it ranges from 17 to 60 mg/L water is slightly hard, with hardness range of 60 to 120 mg/L the water is moderately hard, if in range of 120 to 180 mg/L the water is considered to be hard and if hardness values exceeds 180 mg/L it is regarded as very hard (Durfor & Becker, 1964). During the present study range of TH was reported to be 190.4 ± 46.27 mg/L which indicates that the water quality of Manasbal Lake is very hard which might be due to the presence of excess Ca, Mg, Cl, carbonates, bicarbonates etc. from different sources in the lake. The maximum hardness was found during the summer season (235.6 ± 21.95 mg/L) which may be due to increased agricultural, household and mining activities during this season leading to addition of more agricultural wastes, sewage, Ca and Mg ions into the water body. High concentration of TH was reported at Site III which is in direct contact with nearby village (Kondbal) where most of the agricultural, domestic and mining activities to extract lime stone and dolomite take place. Our results are supported from the studies conducted by Das (2001), Naik et al. (2015) and Gudoo et al. (2018), reporting high hardness values from respective water bodies. Gudoo et al. (2018) reported similar spatial trends in water hardness of Mansbal Lake, with the site nearby Kondbal showing high values of water hardness.

Electrical conductivity is the capacity of a substance to conduct electric current and is mainly an indication of the level of nutrients present in a water body. It usually depends on the amount of dissolved ions present in a water body (Tabassum et al., 2018). According to Rawson (1960) values of specific conductivity above 200 µs/cm indicate a high proportion of nutrients in the water body. During the present study the range of EC was found to be high i.e 282.8 ± 62.77 µs/cm with maximum EC values during the summer season (339.8 ± 27.83 µs/cm) which is mostly due to high runoff of heavy metals, sewage etc. during summer as well as increase in decomposition of organic matter with increased temperature. Further according to Olsen (1950) water bodies with EC range greater than 500 µs/cm have been designated as eutrophic ones from which it can be concluded that Manasbal Lake can be categorized as a mesotrophic water body but it is facing a high nutrient load due to anthropogenic activities (Naik et al., 2015; Sarwar & Majid, 1997).

Total dissolved solids in an aquatic habitat involve both organic and inorganic particles and compounds dissolved in it. Main components comprising the TDS in a water body include chlorides, sulfates, carbonates, bicarbonates, calcium, magnesium, nitrates etc. (Allan & Castillo, 2007). TDS is directly related to the conductivity in a water body. During the present study TDS was found to be maximum during summer and at Site III owing to increased runoff from the surrounding areas as well as increased agricultural and mining activities. Others of the similar view include Bhat et al. (2013) and Reddy et al. (2015), reporting an increased TDS level during summer season

Phosphorus is known to be a primary element resulting in deterioration of a water body by causing excessive growth of aquatic vegetation and leading to eutrophication (Fetahi, 2019). It has a principle role in limiting the primary production in a water body (Bhat et al., 2013). Phosphorus finds its way into the water bodies mainly through the domestic and household waste water, fertilizers used in agricultural fields and disposal of industrial effluents into the water bodies (Vyas, Mishra, Bajapai, Dixit, & Verma, 2006). During the present study the range of TP was reported to be 136.1 ± 43.15 µg/L with its maximum concentration found during summer season at Site III due to direct disposal of domestic, agricultural and industrial wastes into and around the lake. Our results are in agreement with Pandit and Yousuf (2002), Pejaver and Gurav (2008), Reddy et al. (2015) and Hassan et al. (2018), who reported similar causes for an enhanced level of phosphates in water bodies.

Nitrate is an inorganic form of nitrogen in a water body present mainly because of the nitrification process of bacteria which acts on the nitrogen rich water coming from different sources like household sewage or agricultural runoff and through oxidation of ammonical nitrogen to nitrates (Toetz, 1981; Wetzel, 1983). Nitrates are the most common form of inorganic nitrogen found in an aquatic ecosystem. High concentration of nitrates in a water body lead to more planktonic growth (Mlitan, Abofalga, & Swalem, 2015). During the present study high range of nitrate was reported during summer season (183.8 ± 27.94 µg/L) at Site II which might be due to increase in nitrogenous waste disposal from domestic and agricultural sources along with more macrophytic growth and undergoing decomposition process at the deeper levels. Naik et al. (2015) agree with our findings, reporting higher nitrate values toward the outlet of the lake.

Nitrite is an unstable and intermediate product formed during the nitrification and denitrification process by the bacteria. Nitrites are usually reported in low concentration in the aquatic ecosystem because of its unstable nature as it gets converted into nitrates within limited time period (Kroupova, Machova, & Svobodova, 2005). Its concentration is increased mostly by increase in disposal of industrial wastes like metals, dyes etc in the water bodies (Pitter, 1999). In our study the concentration of nitrite was reported to be quite low in all the seasons and sites as well. During summer season overall increase in nitrite concentration was reported which might be due to increase in more disposal of nitrogenous wastes into the lake and further by ongoing process of nitrification and denitrification which increases with increase in temperature. The earlier studies carried out by Dar et al. (2013) and Olalekan et al. (2015) confirm our results.

As per the standards of BIS (2012), all the water quality parameters reported from Mansbal Lake are well within the permissible limits. Moreover as per Prakash, Dwivedi, and Raju (2010) the water quality parameter of Manasbal Lake are well within the ideal value range prescribed for aquaculture.

Regression analysis of physicochemical parameters

Regression is a useful tool to reduce the uncertainty in knowing about the relationship between the different physicochemical parameters to assess the water quality of a given water body (Priya & Arulraj, 2011). The result of the regression analysis yields that either two parameters under study will differ significantly from each other or not. If p < 0.05 the values are significantly different and if p > 0.05 they are not significantly different from each other and the value of regression coefficient (R²) determines the fitness of the model to the given data. During our study regression analysis (Table 4) of different physicochemical parameters indicated that DO showed a significantly negative relationship with WT which may be due to decrease of solubility of oxygen with increase in temperature (Wetzel, 2001). EC was found to have a positive relation with TDS, TP and NO₃-N which is because of increase in concentration of ions in water body (Bhateria & Jain, 2016). EC and TDS were found to have a strongly positive correlation because with increase in TDS, EC also increased significantly. DO showed a weak correlation with the parameters like TP, NO₃-N and NO₂-N because with an increase in nitrogen and phosphorus concentration eutrophication occurs which resulted in more consumption of DO (Shrestha & Basnet, 2018). pH was found to have a negative relation with TH and Alk as changes in ionic balance causes a change in pH (Reddy et al., 2015).

Table 4. Relationship among different physicochemical aspects of Manasbal Lake.

Parameters	Regression equation	R^2	(r) Correlation coefficient	F-value	p-value	Significance
In relation to Water Temperature (WT)
pH	y = 0.004x + 0.899	0.004	0.07	0.318	0.574	Non-significant
Dissolved oxygen	y = −0.293x + 1.258	0.232	−0.48	21.221	0.000	Significant
Total hardness	y = 0.141x + 2.102	0.052	0.23	3.857	0.053	Significant
Electrical conductivity	y = −0.411x + 2.916	0.617	−0.79	113.08	0.000	Significant
Total dissolved solids	y = −0.361x + 2.579	0.601	−0.78	105.59	0.000	Significant
Total phosphorus	y = −0.404x + 2.582	0.354	−0.6	38.44	0.000	Significant
In relation to Total phosphorus (TP)
Dissolved oxygen	y = 0.316x + 0.251	0.124	0.35	9.975	0.002	Significant
In relation to Nitrates (NO3-N)
Dissolved oxygen	y = 0.301x + 0.289	0.086	0.29	6.652	0.012	Significant
In relation to Nitrites (NO2-N)
Dissolved oxygen	y = 0.077x + 0.821	0.018	0.14	1.299	0.258	Non-significant
In relation to Electrical Conductivity (EC)
Total hardness	y = −0.421x + 3.293	0.127	−0.36	10.253	0.002	Significant
Total dissolved solids	y = 0.708x + 0.432	0.63	0.79	119.666	0.000	Significant
Total phosphorus	y = 0.868x – 0.006	0.446	0.67	56.511	0.000	Significant
Nitrates	y = 0.576x + 0.684	0.256	0.51	24.177	0.000	Significant
In relation to Total Hardness (TH)
Dissolved oxygen	y = −0.288x + 1.572	0.085	−0.3	6.534	0.012	Significant
Alkalinity	y = −0.050x + 2.224	0.006	−0.08	0.487	0.487	Non-significant
In relation to pH
Free carbon dioxide	y = 0.706x – 0.056	0.005	0.07	0.359	0.550	Non-significant
Total hardness	y = −0.357x + 2.588	0.001	−0.04	0.116	0.733	Non-significant
Alkalinity	y = −2.278x + 4.172	0.184	−0.43	15.787	0.000	Significant

Multivariate statistical analysis

Cluster analysis (CA)

To know the similarity among the physicochemical parameters at different sites cluster analysis was applied. The dendrogram obtained from the same is depicted in Figure 4 from which it can be seen that two clusters have been obtained, cluster I comprising Site-II and cluster II consisting of Sites-I and III, depicting that the physicochemical parameters of Site-II differ widely with Site-I and III.

Figure 4. Dendrogram showing the similarity and dissimilarity in physicochemical parameters of Manasbal Lake.

Principal component analysis (PCA)

In order to know the impact of different physicochemical parameters on the overall water quality of the Manasbal Lake principal component analysis was carried out. The resulting PCA yielded four principal components (PCs) that accounted for 72.48% (PC 1 = 38.62%, PC 2 = 15.44 %, PC 3 = 9.71% and PC 4 = 8.71%) of the total variance. The first component (PC1) with the eigen value of 4.63 was found to have significantly positive (>0.7) loadings for the parameters like TDS, EC, TP and NO₃-N and significantly negative loadings on WT. The second component (PC2) having the eigen value of 1.85 was found to have a positive loading on pH of the water body where as significantly negative loading was obtained for the Alk and the third principle component (PC3) corresponding to the eigen value of 1.17 was reported to have significantly negative loading on TH only. The forth principal component (PC4) sharing the eigen value of 1.05 possessed a positive loading for FCO₂ and a negative loading for pH. From the principal component analysis the results revealed that the main parameters affecting the water quality in the Manasbal Lake include TDS, EC, TP, NO₃-N, pH, FCO₂, DO and Alk (Figure 5). Strong positive loadings on TDS, EC, TP, NO₃-N can be attributed to different pollution sources in the form of household, agricultural and domestic wastes being drained into the lake and the mining activities around the lake which lead to the increase in organic and inorganic components in the water body. Our results are in agreement with the studies of Arafat et al. (2022), reporting strong positive loadings on TDS, EC and NO₃-N

Figure 5. Loading plots of four Principal components formed during Principal component analysis of physicochemical parameters of Manasbal Lake.

Fish assemblage in Manasbal Lake

During the present study a total of 22,522 fish specimens were reported which belonged to 7 species and 2 families. Family Cyprinidae was found to contribute maximum in the fish catch from Manasbal Lake (64%) followed by Gambusia holbrooki from family Poeciilidae (36%) (Figure 6). From the family Cyprinidae Pethia conchonius (34%) and Crossocheilus diplochilus (22%) were abundantly reported. Similar results on the fish abundance from the Manasbal Lake were reported by Andrabi, Bakhtiyar, Parveen, and Arafat (2022).

Figure 6. Fish fauna composition of Manasbal Lake.

Relationship between physicochemical characteristics and fish assemblage

The distribution of the fish fauna in the Manasbal Lake was significantly impacted by the water quality. Variation in the fish fauna captured was reported from the different sampling sites chosen for this study, indicating different habitat preferences of the fish fauna. So to assess the distribution of the fish species with respect to its water quality aspects Pearson’s correlation (PC) and canonical correspondence analysis (CCA) was carried out. From the analysis of CCA biplot (Figure 7) the fish fauna of Manasbal Lake was distinguished into four groups. Species like Schizothorax niger and S. curvifrons have positive loadings on both the axis (Axis-1 and Axis-2) and are mostly influenced by pH and nitrate-nitrogen concentration of this water body. The same is reflected from the Pearson’s correlation table (Table 5) wherein a strong positive correlation was found between the abundance of S. niger and S. curvifrons with pH of the water body and a weak positive correlation was reported between the two species and the nitrate-nitrogen concentration. The second group comprised of species having a positive score on Axis-1and a negative loading on Axis-2, that included Carassius carassius and Cyprinus carpio (C. carpio var. communis and C. carpio var. specularis). These were slightly impacted by the pH of the water body but on the other hand showed a negative correlation with dissolved oxygen of the water body. The third group was formed by the species Crossocheilus diplochilus and Pethia conchonius with negative score on Axis-1 and positive score on Axis-2 and the main water quality parameters affecting their distribution were reported to be water temperature and free carbon dioxide with which they showed a weak positive correlation whereas a negative correlation was reported between these fish species and pH and nitrate-nitrogen concentration of the lake. The fourth group included Gambusia holbrooki having a negative score on both axis and showing a strong positive correlation with water temperature and strong negative correlation with total dissolved solids, total phosphorus and nitrate-nitrogen concentration.

Figure 7. Canonical correspondence analysis plot showing distribution of fish fauna with respect to environmental variables in Manasbal Lake.

Table 5. Pearson’s correlation table showing relation between physicochemical parameters and fish fauna of Manasbal Lake.

	Crossocheilus diplochilus	Pethia conchonius	Gambusia	S. niger	Carassius carassius	Cyprinus carpio communis	Cyprinus carpio specularis	S. curvifrons
Water Temperature (°C)	.450	0.362	0.621	−0.347	0.236	0.059	0.130	−0.364
Dissolved Oxygen (mg/L)	0.183	0.312	−0.025	−0.129	−0.635	−0.488	−0.531	−0.001
pH	−0.414	−0.524	−0.152	0.607	0.133	0.444	0.279	0.613
Free carbon dioxide (mg/L)	0.371	0.453	0.340	−0.588	−0.052	−0.323	−0.143	−0.581
Alkalinity (mg/L)	0.101	0.164	−0.044	0.069	−0.219	−0.125	−0.098	0.065
Chloride (mg/L)	0.011	−0.029	0.079	0.168	0.111	0.238	0.212	0.195
Total Hardness (mg/L	−0.025	−0.114	0.141	−0.073	0.178	0.085	0.052	−0.011
Total Dissolved Solids (mg/L)	−0.430	−0.319	−0.589	0.234	−0.275	−0.143	−0.212	0.273
Electrical Conductivity (µs/cm)	−0.359	−0.292	−0.623	0.316	−0.193	−0.024	−0.112	0.382
Total Phosphorus (µg/L)	−0.326	−0.260	−0.524	0.240	−0.239	−0.121	−0.219	0.314
Nitrates (µg/L)	−0.587	−0.563	−0.675*	0.468	0.049	0.190	0.094	0.475

So the overall distribution and abundance of fish fauna in a water body is dependent on different abiotic and biotic factors. For the proper establishment and flourishing of a fish population optimum environmental conditions are pre-requisite. Among the abiotic ones the quality of water and the different parameters governing them are worth mentioning like DO, WT, FCO₂ etc (Kadye, Magadza, Moyo, & Kativu, 2008). Alteration in the environmental or habitat conditions results in either dislocation of the organisms to other habitats or lead to their extinction. The variability of water quality parameters in an aquatic habitat have a direct relationship with the kind of fish fauna inhabiting it (Langerhans, Layman, Langerhans, & Dewitt, 2003; Magnuson et al., 1998). According to Harding (2003) abiotic factors are having a marked impact in structuring the fish community of a water body along with the biotic parameters. The CCA and PC revealed the direct impact of different physicochemical variables on the distribution of the fish fauna in the lake. The main impacting parameters were reported to be pH, WT, FCO_2, NO₃-N and DO. Some other parameters like EC, TP, TDS and Cl⁻ were seen to show less marked impacts on the distribution of fish species. Further it was seen that among the selected sites, Site-I and Site-III were reported to have greater impact of DO, FCO₂ and WT thus the fish fauna is represented mostly by small fishes like P. conchonius, C. diplochilus and G. holbrooki while as fish fauna at Site-II was restricted by pH and NO₃-N and the fish species present were C. carpio var. communis, C. carpio var. specularis, C. carassius, S. niger and S. curvifrons. Different workers have worked on the impact of environmental variables on the community structure and distribution of fish fauna in other water bodies. Shuter, MacLean, Fry, and Regier (1980) and Grossman et al., (1998) reported temperature to be limiting factor in restricting the species distribution in different aquatic habitats. Mensah et al. (2018) attributed 43.30% variation in species abundance to environmental factors, with TDS, nitrates and water level being the main factors affecting the fish community structure. Glińska-Lewczuk et al. (2016) reported 22.6% variance in fish population attributable to environmental factors, with nitrate and phosphate explaining significant oortion of this variance.

Also the variation of the fish fauna in the Manasbal Lake with reference to habitat preference and water quality parameters is clearly shown by the NMDS plot (Figure 8) wherein it can be seen that fish fauna of Site-I and Site-III show similarity in comparison to that of Site-II which can be attributed to the similarity in water quality aspects. Again the cluster analysis using HAC revealed the formation of two major clusters relating to the distribution of fish fauna with respect to physicochemical aspects of Manasbal Lake (Figure 9). Cluster I showing similarity in water quality of Site-I and Site-III and the dominance of fish species like, P. conchonius, C. diplochilus and G. holbrooki whereas cluster II having difference in water quality at Site-II with dominance of species like C. carpio, C. carassius, S. niger and S. curvifrons.

Figure 8. NMDS plot showing distribution of fish fauna with respect to sites in Manasbal Lake.

Figure 9. Dendrogram showing distribution of fish fauna with respect to variation in physicochemical aspects of Manasbal Lake.

Conclusion

The present study demonstrates the requirement and value of doing multivariate statistical analyses on huge, intricate databases in order to learn more about the quality of surface water and its impact on the fish fauna distribution. The aim of the present study was to have an in-depth analysis of physicochemical parameters of the Manasbal Lake, which is the deepest fresh water lake in India, and to know the impact of these parameters on the distribution and abundance of fish fauna. The results revealed that the physicochemical characteristics varied on seasonal and spatial basis and the parameters including, TDS, EC, TP, NO₃-N, pH, FCO₂, DO and Alk were the ones that reflected the changes in the water quality of the lake. The distribution of the fish fauna was mainly affected by the parameters pH, WT, FCO_2, NO₃-N and DO. Also during the present study it was revealed that the water quality and the type of fish fauna at two sampling sites (Site-I and Site-III) were quite similar as compared to the third sampling site (Site-II). Overall the water quality in the Manasbal Lake is favorable for the flourishing of the aquatic fauna as all the respective water quality parameters are under the limit, still a continuous monitoring of both the aspects is necessary because of increasing anthropogenic pressures and changing climatic conditions.

Acknowledgments

The authors are highly grateful to the Head, Department of Zoology, the University of Kashmir for providing all the necessary facilities during the present study and one of the authors (Yahya Bakhtiyar) is thankful to the Science and Engineering Research Board, Department of Science and Technology, Government of India (File No. EMR/2017/003669) for providing financial assistance for the establishment of the laboratory where the work was conducted.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data collected during the current study will be available from the corresponding author on reasonable request.

Additional information

Funding

This work was supported by the funding associated.