The study of correlation between physico-chemical parameters and abundance of Barilius bendelisis in three rivers at different seasons

Abhisek Saha^1*, Debashis Das² and Gobinda Chandra De^{3 *}Correspondence: Abhisek Saha, Department of Chemistry, Tufanganj College, West Bengal 736160, India, Email:

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Introduction

Northern part of West Bengal, popularly known as North Bengal is gifted with numerous torrent fresh water rivers; the river “Torsa, Mansai (Jaldhaka)” are popular among them. There are six major river systems longitudinally cut the Cooch behar district flowing in a south-easterly direction. From the west to east these are the Tista, Jaldhaka, Torsa, Kaljani, Raidak and Gangadhar (Sonkosh) system. Some notable tributary rivers are Dharla, Jaldhaka, Raidak–II, Dudua, Kaljani, Sankosh, Gadadhar, Mansai, Ghargharia Jorai etc., [1].

River Torsa situated in the Cooch Behar district covers a stretch of about 61 Km up to the lower reaches of the river. The Torsa River has a total length of about 354.42 km, and runs down through the districts of Jalpaiguri, Alipurduar and Cooch Behar, originating from Chumhi valley in Tibet (China) is a Trans-Himalayan river in true sense. The Torsa River flows into Bangladesh as the Kaljani and meets the Jamuna there. River Raidak-1 situated in Cooch Behar district covers a stretch of about 59.20 Km up to the lower reaches of the river. The Raidak-1 river has a total length of about 90 km and runs down through the districts of Alipurduar and Cooch Behar. The river flows from the ice field of the Jomolhari Peak (7270 m)-Kungphu (6894 m)-Takaphu (6493 m) of Himalaya in Bhutan. Raidak's source is located at an elevation of 6400 meters.  Within the Bhutanese territory, the headstream of the Raidak is known as Wong-Chu. It receives two major tributaries the Paro Chu and the Ha Chu. The catchment region has an area of 5505.2 square kilometers, of which 4813 square kilometers are located in Bhutan. 692 sq. km within the sub-Himalayan northern part of West Bengal and only 450 sq. km is situated within the Alipurduar district. The Raidak meets the Brahmaputra at a stretch of 327 kilometers in Bangladesh's Kurigram District, where it is also known as the Dudhkumar River. Raidak-1 joins the united stream of Torsa and Kaljani. Jaldhaka river is known as the Mansai river in the Mathabhanga region of the Cooch Behar district, has a total length of about 192 km., and runs down through the districts of Darjeeling, Jalpaiguri, and Cooch Behar of West Bengal, India originating from Bitang Lake in Sikkim at an altitude of 4250 m to 4550 m which is known as Dichu in Bhutan. River reach at Cooch Behar district from the northwest in Dhulia Baldiahati of Mekhliganj Subdivision of Cooch Behar. It enters Bangladesh at Barabangla in the Dinhata Subdivision and meets the Brahmaputra. The river is also known as Mansai, Singhimari, and Dharala in the different locations of Cooch Behar district. The portion of the river which is called Mansai in the area of Mathabhanga subdivision of Cooch Behar district of West Bengal. The Jaldhaka is known as Mansai at Mathabhanga subdivision of Cooch Behar district and Singimari at Dinhata subdivision in Cooch Behar district of West Bengal of India. The total length of the river is 192 km, among which 98 km is in the District.

Barilius bendelisis is a tropical freshwater species known locally as 'Boroli' and has economic importance because of the ornamental value and prospective food fish [2]. Tropical freshwater fish Barilius bendelisis [3] found in the Torsa, Teesta, Mansai (Jaldhaka), Raidak-1, and adjoining rivers of northern-West-Bengal, India. The Barilius bendelisis is beautiful silver-colored with bright blue bands having peaceful nature with barbles is considered as indigenous fish. Barilius bendelisis has been ranked as least concern IUCN ver 3.1 (last assessed 26 May 2021) [4] but in Himalayan drainages, it wants effective conservation actions [5]. According to the CAMP Report on freshwater fish of India, the conservation status of this Barilius species is indicated as 'Lower Risk near Threatened' (LRnt) [6].

The abundance of these hill touts is declining as a result of overfishing using non-scientific fishing practices (poisoning of stream water, electric current, hammering, etc.). However, despite economic and ecological importance, Barilius bendelisis is facing a rapid reduction in India, especially in eastern parts due to overfishing, habitat loss, hydrologic modification, and water pollution [7]. For example, in recent years, Barilius bendelisis has become infrequent in Torsa, Mansai (Jaldhaka), and Raidak-1 river at Cooch Behar region of West Bengal and adjoining rivers of northern-West Bengal, India [8].

The present status of the Barilius bendelisis is mainly because of the deterioration of the environment particularly, water quality which may be due to agricultural run-offs or pesticide effects of tea gardens and various anthropogenic activities in the Terai and Dooars regions of West Bengal, India. In the northern region of West Bengal, India, Barilius species are regarded as a good choice for eating fish [9]. In the region of the present study occurrence of Barilius species is becoming low throughout the year.

Barilius bendelisis represent a vital part of the protein diet of the countryside human population residing in the neighborhood of the stream banks and the neighboring locality. Immediate rehabilitation of Barilius species is important from its extinction from the environment. Barilius bendelisis conservation will provide a permanent protein source for fishing people and other residents. Studying this species and its identification at the molecular level is in an urgent need. Therefore Barilius bendelisis were selected for this research study. Live fishes of Barilius bendelisis were collected from different sampling sites of Torsa, Raidak-1, and Mansai river of Cooch Behar district of West Bengal and immediately oxygen packed in sterile polythene bags and transported to the laboratory. The basin of these rivers sustains life and livelihoods of farmers, fishermen and slum-dwellers. Farmers consume the water resource for cultivation and drain off the utilized excess water which carries varieties of pesticides and fertilizers to that river [10,11]. The fishermen utilize the downstream of these rivers for fishing [12]. Slum-dwellers exploit the water resource for bathing, washing of cloths etc. Sewage from municipality, garbage from market directly discharges to this river. As a consequence the physical, chemical and biological characteristics of the river water are gradually changing and producing the harmful effect on aquatic biota and thereby human beings due to biomagnification. A quantity of physico-chemical variables of the water along with the abundance of the Barilius bendelisis were studied to get an adequate knowledge [13] of their oscillating rhythmic phenomena, and to throw a close insight into the environment of the system. A considerable quantity of research has been carried out on the physicochemical parameters of riverine water and their impact on aquatic biota in India [14-18]. However, this type of study has not been carried out in respect in Raidak-I river of West Bengal. The objectives of this study is to investigate physical and chemical properties of this river water in different seasons of the year and to examine the density and diversity of captured fin-fish resources from the river so as to find the relation in between the fish population with hydrological parameters to get a picture of the effect of pollution if any.

Materials and Methods

Sampling site

Barilius bendelisis collected from fishermen landing at the bank of the Torsa, Raidak-1, Jaldhaka (Mansai) river of Cooch Behar district of West Bengal (Figure 1). It is necessary to document a comprehensive nutrient profile with a specific focus on popular Small Indigenous Species (SIS) Barilius bendelisis in Cooch Behar for pre-monsoon, monsoon and the post-monsoon period during the period of March 2018 to November 2019 in different spots of each river (Table 1). The collected fish samples were transported in an insulated icebox with a proper identification mark to the laboratory.

Figure 1: Landscape visualization of the Torsa, Raidak-1, and Mansai (Jaldhaka) river systems' origins and networks, together with sampling locations.

Fishing techniques used for fishing in Torsa, Raidak-1, and Mansai (Jaldhaka) river

The fish were caught in the Torsa, Raidak-1, and Mansai (Jaldhaka) rivers at three different locations using a cast net (mesh size 6 mm × 6 mm) or a vessel net or Khara Jal (mesh size 6 mm × 6 mm.) and a gillnet (variable mesh sizes) and other conventional techniques with the support of trained local fishermen, as recommended [19,20].

Collection procedure of river water

Water samples were taken at three seasons of the year for physicochemical parameter analysis, which was done following [21], viz. pre-monsoon (March to May), monsoon (June to September), retreating monsoon (October to November). Random samples of water were collected from all sampling sites (Figure 1) used in the morning of the first week of every month between the periods of 6.30 am to 8.30 am. Nineteen Physico-chemical parameters were undertaken for a detailed investigation. The monthly average was calculated by combining all fifteen-day samples. All water samples were collected in duplicate form by two glass DO (Dissolved Oxygen) bottles with the capacity of 300 ml each and one large PVC (1 litter capacity) bottle. Immediately the water samples were transferred to the departmental laboratory for all physicochemical studies except the air, water temperature, pH, conductivity and Total Dissolved Solids (TDS). A simple mercury thermometer was used to measure the air temperature at 1 ft. above surface water and the water temperature was measured with the same thermometer by placing it inside the water at the depth of 1 ft. on the three sampling stations (Table 1). The depth of the water body was measured by a marked (in ft.) wooden stick at the time of sampling. Other physicochemical parameters were examined in the Chemistry laboratories of Tufanganj Mahavidyalaya in Cooch Behar and Cooch Behar Panchanan Barma University in Cooch Behar, India, except for BOD; all tests were performed on the same day as early as possible (within 2-3 hours).

Table 1 : GPS location of sampling spots of Barilius bendelisis.

Experimental procedures

Water quality: Water samples for Physico-chemical analysis of water were collected from the experimental areas at monthly intervals during the study period. All the Physico-chemical parameters have been analyzed using the standard method [22-24].

Statistical analysis: The statistical investigation was done utilizing SPSS 21, PAST 4.03, MS Excel 2007 software.

Ethical issues: The examination was as per the Declaration of Helsinki and guidelines on good clinical practice locally accessible. It was likewise endorsed by the institutional ethics board and morals committee [25].

Results

Physico-chemical parameters of River Torsa at ST1, ST2, and ST3 were observed during 2018-2019, and the mean value of each parameter is calculated which is summarized in the following table (Tables 2-4).

Table 2:  Physico-chemical parameters of Torsa River at ST1, ST2, and ST3 during the period 2018-19.

Table 3:  Physico-chemical parameters of Mansai (Jaldhaka) River at SJ1, SJ2, and SJ3 during the period 2018-19.

Table 4 : Physico-chemical parameters of Raidak-1 river at SR1, SR2, and SR3 during the study period.

Monthwise comparative study of average CPUE at different spots

Monthwise average CPUE of Barilius bendilisis at different sites of three rivers during the period of 2018-2019 was recorded. From the graphical representation, it is found that the average CPUE is maximum (Average CPUE=23) at ST1 of Torsa river in October and November and minimum (Average CPUE=4) at SR1 of Raidak-1 river in September (Figure 2).

Figure 2: Graphical representation of months' average CPUE of Barilius bendelisis at ST1, SJ1, and SR1.

From the graphical representation, it is found that the average CPUE is maximum (Average CPUE=4) at SJ2 in April, October, and November. At ST2, CPUE is also maximum in October and minimum (Average CPUE=1) at SR2 of Raidak-1 river in March and May. At ST2 also showed a minimum count in April and May and at SJ2 in August (Figure 3).

Figure 3: Graphical representation of months' average CPUE of Barilius bendelisis at ST2, SJ2, and SR2.

From the graphical representation, it is found that the average CPUE is maximum (Average CPUE=21) at ST3 of Torsa river in November and minimum (Average CPUE=3) at SR3 of Raidak-1 river in July and September (Figure 4).

Figure 4: Graphical representation of months' average CPUE of Barilius bendelisis at ST3, SJ3, and SR3.

Among the three rivers average CPUE (23) is maximum at ST1 of Torsa River in October and CPUE (1) is minimum at ST2 of Torsa River in March, April, and May whereas the same value was obtained for the Raidak-1 River at SR2 in March and May and SJ2 of Mansai river in August.

Statistical analysis on physico-chemical parameters of Torsa, Raidak-1, and Mansai (Jaldhaka) river with CPUE of Barilius bendelisis

Two way factorial ANOVA: To explain observed s in CPUE for both sampling years (2018 and 2019), the data were treated to a two-way factorial ANOVA with sampling sites and seasons (Pre-monsoon, monsoon, and post-monsoon) as predictor variables. Results suggested that the CPUE of Barilius bendelisis varied significantly with the variables at the P<0.05 level. All F values are significant at the P<0.05 level.

Limnology correlation (2018 and 2019): Limnology Correlation was calculated for two consecutive years and represented below (Tables 5 and 6). Correlation is significant at the 0.01 level (2-tailed). And Correlation is also significant at the 0.05 level (2-tailed) in both years.

Table 5: The correlation matrix for Physico-chemical parameters based on limnology data collected in 2018.

Table 6:  The correlation matrix for Physico-chemical parameters based on limnology data collected in 2019.

Regression analysis on limnology: Further, both the year's data (2018 and 2019) were also subjected to regression analysis concerning Physico-chemical parameters viz. Air temperature, Water temperature, Turbidity, pH, TDS, TSS, Total solid, Depth, Conductivity, DO, Free CO2, BOD, Nitrate, Phosphate, Chloride, Total hardness, and Total alkalinity and abundance CPUE of Barilius bendelisis (Figures 5 and 6).

Figure 5: The values (mean ± S.E.) of physicochemical parameters and CPUE of Barilius bendelisis: Based on data collected in the year 2018.

Figure 6: The values (mean ± S.E.) of physicochemical parameters and CPUE of Barilius bendelisis: Based on data collected in the year 2019.

The model suggests for the year 2018, R-value, R Square, Adjusted R Square is, Std. Error of the Estimate and the value of Durbin-Watson was 0.821, 0.673, 0.635, 3.476, 1.132 respectively. The model suggests for the year 2019, R-value, R Square, Adjusted R Square, Std. Error of the Estimate and the value of Durbin-Watson was 0.818, 0.670, 0.631, 3.714 and 1.239 respectively. R square values for both the years considered a moderate effect size. The value of Durbin-Watson is below 2, it generally indicates a positive autocorrelation.

Coefficients calculation: Unstandardized Coefficients and Standardized Coefficients were calculated in two consecutive years.  From Collinearity Statistics, Tolerance and VIF were also calculated for AT, WT, Turbidity, pH, TDS, TSS, TS, Depth, Conductivity, DO, Free CO2, BOD, Nitrate, Phosphate, Chloride, TH, TA. The degree of interrelation among the Physico-chemical parameters with abundance CPUE of Barilius bendelisis is represented through, the Pearson correlation matrix (Tables 7 and 8).

Table 7: The degree of interrelation (Pearson correlation matrix) among the Physico-chemical parameters and abundance (CPUE) of Barilius bendelisis: Based on the year 2018.

Table 8: The degree of interrelation (Pearson correlation matrix) among the Physico-chemical parameters and abundance (CPUE) of Barilius bendelisis: Based on the year 2019.

Collinearity diagnostics: Collinearity Diagnostics were done in two consecutive years. For the two consecutive years, several eigenvalues are near zero, suggesting that the predictor variables are highly correlated. The following equation revealed the relationship: y=1/(1+exp (–(a+b1 × 1–b2 × 2–b3 × 3–b4 × 4–b5 × 5–b6 × 6–b7 × 7–b8 × 8–b9 × 9–b10 × 10–b11 × 11–b12 × 12–b13 × 13–b14 × 14–b15 × 15–b16 × 16–b17 × 17))); where y represents the CPUE of Barilius bendelisis, × 1 to × 17 denotes all the above mentioned physico-chemical parameters.

Discussion

The abundance of Barilius bendelisis in the Torsa river at three spots in three seasons was observed in two consecutive years in terms of CPUE of the fishes and at ST1, CPUE in the pre-monsoon, monsoon, and post-monsoon period was in the range (7-12), (4-10) and (20-25) respectively. At ST2, CPUE in the pre-monsoon, monsoon, and post-monsoon period was in the range (1-4), (2-4), and (3-5) respectively. At ST3, CPUE in the pre-monsoon, monsoon, and post-monsoon period was in the range (6-10), (5-8), and (18-22) respectively. The abundance of Barilius bendelisis in Mansai (Jaldhaka) river at three spots in three seasons was observed in two consecutive years in terms of CPUE of the fish and at SJ1, CPUE in the pre-monsoon, monsoon, and post-monsoon period was in the range (6-10), (5-9) and (20-22) respectively. At SJ2, CPUE in the pre-monsoon, monsoon, and post-monsoon period was in the range (2-6), (1-5), and (3-6) respectively. At SJ3, CPUE in the pre-monsoon, monsoon, and post-monsoon period was in the range (6-12), (6-11), and (15-25) respectively. The abundance of Barilius bendelisis in Raidak-1 river at three spots in three seasons was observed in two consecutive years in terms of CPUE of the fish and at SR1, CPUE in the pre-monsoon, monsoon, and post-monsoon period was in the range (6-9), (4-8) and (19-22) respectively. At SR2, CPUE in the pre-monsoon, monsoon, and post-monsoon period was in the range (1-2), (2-4), and (2-4) respectively. At SR3, CPUE in the pre-monsoon, monsoon, and post-monsoon period was in the range (7-10), (2-5), and (16-19) respectively. For the first year (2018), the value of the correlation coefficient (r) was found highest between pH and Total suspended solid (r=0.97), followed by that of Total suspended solid and Total solid (r=0.77) and pH and Total solid (r=0.73). However, for the subsequent year (2019), r was found to be highest between pH and Total suspended solid (r=0.98) followed by Air temperature and Water temperature (r=0.89) and Total suspended solid and Total solid (r=0.77) All these values were positively significant at 0.01 level (2 tailed).

Conclusion

The water quality parameters that were considered in the present observation were found within the range of standard limit for the survival of fishes and also within the range of drinking water standard with some limitations. Among the study sites, ST2, SR2, SJ2 were identified as the polluted sites out of the nine observation sites during the period of study. Anthropogenic activities might be responsible for the deterioration of the above-mentioned polluted sites. The results of the present study are based upon the observations (n=54) carried out through field sampling between March 2018 to November 2019, and expressed as Catch Par Unit Effort (CPUE). To explain observed changes in CPUE for both sampling years, the data were treated to a two-way factorial ANOVA with sampling locations and seasons as predictor variables. Results suggested that the CPUE varied significantly with the variables at the PV<0.05 level. In cases where the variables did not vary significantly, it may be attributed to the independent/interdepend variation of the variables. Further, both the years’ data were also subjected to regression analysis concerning Physico-chemical parameters viz. Air temperature, Water temperature, Turbidity, pH, TDS, TSS, Total solid, Depth, Conductivity, DO, Free CO2, BOD, Nitrate, Phosphate, Chloride, Total hardness, and total alkalinity.

Acknowledgement

The authors acknowledge the Head, Department of Chemistry, Cooch Behar Panchanan University, Cooch Behar-736101 and Principal, Tufanganj College, Cooch Behar-736160 for providing necessary laboratory facilities for carrying out the research work.We are also thankful to Dr. Soumyajit Banerjee from the Department of Zoology, Serampore College, Hooghly, West Bengal for helping in statistical work. It is our great pleasure to express sincere thanks to Prof. Goutam Kumar Saha, Department of Zoology, University of Calcutta. We are also thankful to Prof. Ashis Kumar Saha, Remote Sensing GIS from the Universty of Delhi for his help to create the location map of sampling.

Conflict of Interest

The authors declare that they have no actual and potential conflict of interest.

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