Spatial and temporal variations in physicochemical parameters
The physicochemical parameters were compared site wise (spatial variations) as well as during different seasons (temporal variations). The mean values of the physicochemical parameters studied for the three sites Okhla Bird Sanctuary (OBS), Sanjay Lake (SL) and Raj Ghat (RJ) pond for different seasons are given in Table 1 and Fig. 2.
Table 1
Physicochemical parameters (mean ± SD) of Okhla Bird Sanctuary (OBS), Sanjay Lake (SL) and Raj Ghat Pond (RJ), Delhi recorded during the study period.
Parameters (n = 3) | Sites | Sept 2018 | Nov 2018 | Jan 2019 | Mar 2019 | May 2019 | July 2019 |
Temperature (inside water) (ºC) | OBS | 28 ± 1 | 22 ± 1 | 14 ± 1 | 23 ± 1 | 30 ± 1 | 33 ± 1 |
SL | 29 ± 1 | 24 ± 1 | 16.3 ± 1.5 | 25 ± 1 | 30 ± 1 | 35.3 ± 0.57 |
RJ | 29 ± 1 | 25.3 ± 1 | 18 ± 1.5 | 25 ± 1 | 32 ± 1 | 35 ± 1 |
Temperature (atmospheric) (ºC) | OBS | 30 ± 1 | 25 ± 1 | 15 ± 1 | 25.3 ± 1.57 | 32.6 ± 0.57 | 35.3 ± 1.52 |
SL | 30 ± 1.15 | 25 ± 0.57 | 18 ± 1 | 28 ± 1 | 32 ± 1 | 36 ± 1 |
RJ | 30 ± 1 | 26 ± 1 | 20 ± 1.52 | 28 ± 1 | 33 ± 1 | 36 ± 1 |
pH | OBS | 7.7 ± 0.01 | 7.38 ± 0.12 | 7.34 ± 0.13 | 7.39 ± 0.04 | 7.77 ± 0.08 | 6.85 ± 0.12 |
SL | 7.7 ± 0.02 | 8.0 ± 0.11 | 7.7 ± 0.04 | 7.8 ± 0.08 | 7.6 ± 0.08 | 7.7 ± 0.12 |
RJ | 7.8 ± 0.09 | 8.3 ± 0.02 | 7.8 ± 0.1 | 8.1 ± 0.12 | 8.2 ± 0.15 | 8 ± 0.06 |
Dissolved oxygen (mg/L) | OBS | 2.5 ± 0.5 | 3.3 ± 0.5 | 2.5 ± 0 | 3.8 ± 0.28 | 6.3 ± 0.28 | 2 ± 1 |
SL | 7 ± 1.32 | 4.6 ± 1.15 | 2 ± 0.5 | 4.6 ± 0.57 | 3.3 ± 0.28 | 4 ± 1 |
RJ | 6.33 ± 1.52 | 5 ± 1.8 | 4.8 ± 0.28 | 5.1 ± 0.28 | 6.66 ± 0.57 | 4.83 ± 0.28 |
Total dissolved solids (mg/L) | OBS | 304.3 ± 2.08 | 351.6 ± 2.3 | 272 ± 2.64 | 302.6 ± 2.08 | 353 ± 2.64 | 317.3 ± 2.08 |
SL | 310.3 ± 1.52 | 368 ± 0.57 | 308 ± 0.57 | 416.6 ± 2.08 | 566 ± 2 | 663 ± 2 |
RJ | 573.33 ± 2.08 | 697 ± 2 | 894.6 ± 1.5 | 1180.3 ± 1.5 | 1362.3 ± 2.51 | 931.3 ± 2.3 |
Electrical conductivity (µS/cm) | OBS | 549.3 ± 1.52 | 693.6 ± 1.52 | 542 ± 2 | 592.3 ± 2.51 | 654.6 ± 2.08 | 573.6 ± 1.52 |
SL | 612 ± 1 | 719 ± 2.6 | 729.6 ± 2.08 | 826 ± 1 | 922.3 ± 2.5 | 973 ± 2 |
RJ | 1044 ± 2.64 | 1249.3 ± 3.2 | 1549.3 ± 1.52 | 1688.3 ± 2.08 | 1581.3 ± 2.08 | 1058.3 ± 1.5 |
Water hardness (mg/L) | OBS | 150 ± 0 | 201.6 ± 2.88 | 175.3 ± 4.6 | 164.0 ± 0.98 | 86.8 ± 2.8 | 15 ± 0 |
SL | 90 ± 0 | 215 ± 5 | 197.6 ± 3.78 | 206.5 ± 2.08 | 82.2 ± 222 | 15 ± 0 |
RJ | 229 ± 4 | 286.6 ± 5.03 | 398.3 ± 2.88 | 648.6 ± 2.3 | 182.5 ± 1.64 | 100 ± 0 |
Chloride (mg/L) | OBS | 43.4 ± 1.5 | 64.0 ± 5.41 | 48.6 ± 2.04 | 57.5 ± 3.26 | 94.1 ± 2.8 | 111.8 ± 0.81 |
SL | 60.1 ± 0.36 | 73.4 ± 4.02 | 81.7 ± 5.4 | 116.5 ± 3.62 | 166.1 ± 0.81 | 221.9 ± 0.59 |
RJ | 149.21 ± 0.55 | 194.89 ± 3.55 | 250.1 ± 3.37 | 337.60 ± 2.25 | 445.22 ± 2.38 | 321.85 ± 3.59 |
Sulphate (mg/L) | OBS | 94.5 ± 3.53 | 106 ± 1.76 | 77.7 ± 7.01 | 75.5 ± 6.61 | 82.6 ± 7.83 | 83.5 ± 7.53 |
SL | 89.4 ± 9.85 | 90.1 ± 15.13 | 100 ± 20.13 | 49.7 ± 5.55 | 88.2 ± 7.49 | 176.3 ± 11.84 |
RJ | 177.3 ± 13.56 | 143.5 ± 4.03 | 182.2 ± 12.35 | 373.7 ± 10.59 | 109.4 ± 10.86 | 103.8 ± 10.42 |
Phosphate (mg/L) | OBS | 0.33 ± 0.09 | 2.39 ± 0.06 | 1.61 ± 0.06 | 0.63 ± 0.018 | 0.17 ± 0.02 | 0.12 ± 0.016 |
SL | 1.70 ± 0.179 | 0.06 ± 0.04 | 0.03 ± 0.016 | 0.70 ± 0.143 | 0.06 ± 0.04 | 0.03 ± 0.016 |
RJ | 1.98 ± 0.02 | 0.17 ± 0.016 | 0.04 ± 0.024 | 0.17 ± 0.024 | 0.23 ± 0.04 | 0.36 ± 0.024 |
Nitrite (mg/L) | OBS | 0.38 ± 0.014 | 0.17 ± 0.08 | 0.133 ± 0.028 | 0.090 ± 0.004 | 0.414 ± 0.11 | 0.014 ± 0.004 |
SL | 0.361 ± 0.039 | 0.04 ± 0.002 | 0.047 ± 0.04 | 0.566 ± 0.229 | 0.007 ± 0.008 | 0.008 ± 0.0007 |
RJ | 0.73 ± 0.05 | 0.059 ± 0.026 | 0.106 ± 0.03 | 0.479 ± 0.189 | 0.846 ± 0.02 | 0.029 ± 0.014 |
Nitrate (mg/L) | OBS | 1.89 ± 0.78 | 2.49 ± 0.42 | 2.73 ± 0.26 | 3.07 ± 0.099 | 1.00 ± 0.07 | 1.404 ± 0.07 |
SL | 0.507 ± 0.07 | 0.468 ± 0.419 | 1.17 ± 0.16 | 0.19 ± 0.59 | 1.55 ± 0.64 | 1.76 ± 0.05 |
RJ | 5.34 ± 2.9 | 6.19 ± 0.29 | 1.88 ± 0.234 | 0.89 ± 0.983 | 2.38 ± 0.35 | 0.89 ± 0.79 |
Ammonia (mg/L) | OBS | 5.00 ± 0 | 10.00 ± 0 | 10.00 ± 0 | 10.00 ± 0 | 10.00 ± 0 | 10.00 ± 0 |
SL | 0.16 ± 0.14 | 0.50 ± 0 | 0.50 ± 0 | 5.00 ± 0 | 1.00 ± 0 | 5.00 ± 0 |
RJ | 0.25 ± 0 | 0.50 ± 0 | 0.50 ± 0 | 0.50 ± 0 | 0.50 ± 0 | 0.50 ± 0 |
Lowest and highest values for each parameter are marked with bold letters; n = number of samples. |
Comparison of physicochemical characteristics of the three sites in different seasons using two-way ANOVA suggests that there is a significant difference in pH (F = 11.151, p < 0.005), TDS (F = 24.203, p < 0.005), EC (F = 31.369, p < 0.005), WH (F = 7.800, p < 0.05), chloride (F = 28.982, p < 0.005), and ammonia (F = 52.515, p < 0.005). Other parameters such as TIW, DO, sulphate, phosphate, nitrite and nitrate had no significant variations. Post-hoc Tukey test suggest that pH, TDS, EC, WH, chloride and ammonia of OBS and SL are significantly different from RJ (p < 0.005). Comparison of physicochemical parameters among different months of all three sites using two-way ANOVA suggests that there is a significant difference in TIW (F = 234.99, p < 0.005), WH (F = 4.378, p < 0.05), and chloride (F = 4.293, p < 0.05) in different months. Other parameters such as pH, DO, TDS, EC, sulphate, phosphate, nitrite, nitrate, and ammonia showed no significant difference among different months. Post-hoc Tukey test comparing different parameters individually among different seasons suggests a significant difference in the TIW among all the months (p < 0.005). Rest of the parameters does not show significant variation seasonally when compared individually.
Correlation among various physicochemical parameters with each other was also analysed in the present study. Pearson correlation coefficients suggested positive and negative correlations of physicochemical parameters with each other as given in Table 2. Principal component analysis plot showed that the parameters such as TIW, pH, DO, TDS, EC, WH, chloride, sulphate correlated with each other and phosphate, nitrite, nitrate and ammonia correlated with each other (Fig. 3). pH is positively and directly correlated with factors like temperature (TIW) and DO, as the photosynthetic activity responsible for the assimilation of bicarbonates and carbon dioxides is responsible for the increase in the pH (Manjare et al. 2010). Dissolved oxygen (DO) in water is attributed to the fact that oxygen is dissolved more during the period of catabolic activity by photosynthesis. Temperature has direct influence on DO and the duration of sunlight, since during the summers when the water temperature increases, it increases the amount of photosynthesis and production of O2 thereby increasing the DO levels (Manjare et al. 2010). The electrical conductivity (EC) of the water depends upon the concentration of ions and its nutrient load. EC is the measure of a solution to conduct electricity hence shows positive correlation with temperature (TIW), pH, DO, TDS, WH, chloride, sulphate, nitrite and nitrate, whereas it showed a negative correlation with phosphate and ammonia (Joshi et al. 2009). Water hardness (WH) is contributed from the evaporation of water during summers leaving the water concentrated (Dubey and Ujjania 2013; Yogesh 2020), hence WH showed a positive correlation with pH, DO, TDS, EC, chloride, sulphate, nitrite and nitrate, whereas it showed a negative correlation with TIW, phosphate and ammonia. Total dissolved solids (TDS) include total inorganic and organic solutes of the water such as organic wastes, industrial effluents, calcium, magnesium, chloride, sulphate, nitrate and nitrite (Tajmunnaher and Chowdhury 2017). TDS is positively correlated with TIW, pH, DO, EC, WH, chloride, sulphate, nitrite and nitrate, whereas it showed a negative correlation with phosphate and ammonia. Chloride concentration is influenced by presence of ionic compounds such as sodium, potassium, nitrate and nitrate which ultimately increases the pH and electrical conductivity of the water (Joshi et al. 2009). Chloride showed a positive correlation with TIW, pH, DO, TDS, EC, WH, sulphate, nitrite and nitrate, whereas it showed a negative correlation with phosphate and ammonia. Sulphate accumulation in water leads to increase in pH, total dissolved solids, and electrical conductivity (Asamoah and Amorin 2011; Popoola et al. 2019). In this study, sulphate showed a positive correlation with TIW, pH, DO, TDS, EC, WH, chloride, nitrite and nitrate, whereas it showed a negative correlation with phosphate and ammonia. Phosphate and nitrate show positive correlation with each other since both acts as nutrients for living organisms (Golder and Chattopadhyay 2016). It has been reported that phosphate availability in water decreases with increase in pH since high pH induces phosphorous to bind with other cations forming insoluble compounds (Cerozi and Fitzsimmons 2016). Phosphate showed a positive correlation with DO, nitrite, nitrate and ammonia whereas it showed a negative correlation with TIW, pH, TDS, EC, WH, chloride and sulphate. Ammonia is converted to nitrite and nitrate by nitrifying bacteria due to which ammonium and nitrite show negative correlation in nitritation-dominant period (Sepehri and Sarrafzadeh 2019). Nitrite showed a positive correlation with TIW, pH, DO, TDS, EC, WH, chloride, sulphate, phosphate and nitrate whereas it showed a negative correlation with ammonia. Nitrate showed a positive correlation with pH, DO, TDS, EC, WH, chloride, sulphate, phosphate and nitrite whereas it showed a negative correlation with TIW and ammonia. Ammonia similar to nitrate, act as nutrient along with phosphate showing positive correlation with phosphate but negative correlation with nitrate especially in nitratation-dominant period (Sepehri and Sarrafzadeh 2019). Ammonia showed a positive correlation with phosphate, whereas it showed a negative correlation with TIW, pH, DO, TDS, EC, WH, chloride, sulphate, nitrite and nitrate.
Table 2
Correlation between physicochemical parameters of three sites sampled during one year from September 2018 to August 2019.
Parameters | TIW | pH | DO | TDS | EC | WH | Chloride | Sulphate | Phosphate | Nitrite | Nitrate | Ammonia |
TIW | 1 | | | | | | | | | | | |
pH | 0.110 | 1 | | | | | | | | | | |
DO | 0.349 | 0.620** | 1 | | | | | | | | | |
TDS | 0.291 | 0.642** | 0.464 | 1 | | | | | | | | |
EC | 0.094 | 0.668** | 0.454 | 0.940** | 1 | | | | | | | |
WH | -0.453 | 0.468* | 0.185 | 0.493* | 0.672** | 1 | | | | | | |
Chloride | 0.388 | 0.586* | 0.429 | 0.983** | 0.891** | 0.359 | 1 | | | | | |
Sulphate | 0.008 | 0.384 | 0.228 | 0.612** | 0.718** | 0.778** | 0.530* | 1 | | | | |
Phosphate | -0.222 | -0.283 | 0.139 | -0.322 | -0.310 | -0.053 | -0.375 | -0.130 | 1 | | | |
Nitrite | 0.168 | 0.360 | 0.611** | 0.363 | 0.326 | 0.256 | 0.313 | 0.183 | 0.279* | 1 | | |
Nitrate | -0.098 | 0.143 | 0.087 | 0.076 | 0.179 | 0.110 | 0.034 | 0.115 | 0.275 | 0.087 | 1 | |
Ammonia | -0.111 | -0.731** | -0.426 | -0.546* | -0.609** | -0.369 | -0.511* | -0.380 | 0.253 | -0.173 | -0.026 | 1 |
Values are Pearson correlation coefficients, *correlation is significant at p < 0.05 level and **correlation are significant at p < 0.01 level. TIW = temperature (inside water), DO = dissolved oxygen, EC = electrical conductivity, TDS = total dissolved solids, WH = water hardness. |
Spatial and temporal variations in Ciliate diversity, richness and evenness
Okhla Bird Sanctuary (OBS) exhibited highest diversity, followed by Sanjay Lake (SL) and Raj Ghat pond (RJ) as represented by Shannon, Simpson, Margalef’s and Pielou’s indices in Table 3 and Fig. 4. In OBS, Shannon index (H') was found to be maximum during September 2018 (2.21 ± 0.40) and minimum during March 2019 (1.63 ± 0.22) and May 2019 (1.63 ± 0.49). In SL, Shannon index corresponding to species diversity (H') was found to be maximum in September 2018 (1.64 ± 0.02) and minimum in January 2019 (0.18 ± 0.32). In RJ, Shannon index corresponding to species diversity (H') was found to be maximum in September 2018 (1.33 ± 0.20) and minimum in July 2019 (0.50 ± 0.53).
Table 3
Species diversity, richness and evenness of ciliate community present in Okhla Bird Sanctuary (OBS), Sanjay Lake (SL), Raj Ghat pond (RJ), Delhi during the study period.
Month of collection (n = 3) | Sites | Species diversity | Species richness | Species evenness |
Shannon Index (H') | Simpson Index (D) | Margalef’s Index (d) | Pielou’s Index (J') |
Sep-18 | OBS | 2.21 ± 0.40 | 0.16 ± 0.05 | 3.51 ± 1.36 | 0.48 ± 0.05 |
SL | 1.64 ± 0.02 | 0.23 ± 0 | 1.69 ± 0.31 | 0.36 ± 0.02 |
RJ | 1.33 ± 0.20 | 0.35 ± 0.10 | 1.23 ± 0.15 | 0.28 ± 0.05 |
Nov-18 | OBS | 2.14 ± 0.39 | 0.12 ± 0.06 | 2.46 ± 0.74 | 0.53 ± 0.06 |
SL | 0.80 ± 0.28 | 0.39 ± 0.10 | 0.72 ± 0.215 | 0.38 ± 0.10 |
RJ | 1.05 ± 0.28 | 0.40 ± 0.11 | 0.83 ± 0.315 | 0.29 ± 0.09 |
Jan-19 | OBS | 1.76 ± 0.43 | 0.20 ± 0.09 | 2.07 ± 0.98 | 0.46 ± 0.07 |
SL | 0.18 ± 0.32 | 0.20 ± 0.34 | 0.12 ± 0.20 | 0.06 ± 0.11 |
RJ | 0.93 ± 0.28 | 0.43 ± 0.17 | 0.81 ± 0.17 | 0.32 ± 0.08 |
Mar-19 | OBS | 1.63 ± 0.22 | 0.21 ± 0.045 | 1.57 ± 0.407 | 0.38 ± 0.028 |
SL | 0.90 ± 0.69 | 0.51 ± 0.29 | 0.84 ± 0.59 | 0.27 ± 0.15 |
RJ | 1.07 ± 0.36 | 0.35 ± 0.11 | 0.77 ± 0.33 | 0.32 ± 0.04 |
May-19 | OBS | 1.63 ± 0.49 | 0.21 ± 0.10 | 1.31 ± 0.65 | 0.38 ± 0.07 |
SL | 1.11 ± 0.38 | 0.39 ± 0.19 | 0.98 ± 0.40 | 0.30 ± 0.11 |
RJ | 0.94 ± 0.31 | 0.41 ± 0.11 | 0.47 ± 0.19 | 0.22 ± 0.05 |
Jul-19 | OBS | 1.86 ± 0.52 | 0.19 ± 0.09 | 1.84 ± 1.18 | 0.42 ± 0.100 |
SL | 1.57 ± 0.24 | 0.23 ± 0.07 | 1.25 ± 0.37 | 0.37 ± 0.06 |
RJ | 0.50 ± 0.53 | 0.37 ± 0.35 | 0.30 ± 0.30 | 0.11 ± 0.10 |
Lowest and highest values for each index are marked with bold letters; n = number of samples. |
Comparison of diversity indices among all three sites by two-way ANOVA suggests that there is a significant difference in the species diversity indices, Shannon (F = 12.665, p < 0.005) and Simpson (F = 10.839, P < 0.005), species richness index (F = 17.712, p < 0.005), and species evenness index (F = 6.712, p < 0.05). Post-hoc Tukey test suggests that Shannon and Simpson diversity index, Margalef’s richness index and Pielou’s evenness index of OBS is significantly different from SL and RJ (p < 0.005). Comparison of diversity indices among different seasons in all three sites by two-way ANOVA followed by Post-hoc Tukey tests suggest that there is no significant seasonal difference in the species diversity, richness and evenness indices of all the three sites. Though, ciliate community composition varied during different seasons in the three sites.
In the previous reports the diversity of biological community was studied using the diversity indices as they prove to be an effective way to study the diversity in environmental samples. Various studies such as the ciliate diversity of different sites of river Yamuna (Kaur et al. 2021), the phytoplankton diversity from the coastal regions of Tamil Nadu (Vajravelu et al. 2018), microzooplankton community from the Kochi backwaters (Anjusha et al. 2018), etc were studied using diversity indices. These studies have also suggested that the diversity of microzooplankton communities were significantly high during the pre and post monsoon periods similar to the present study (Anjusha et al. 2018; Vajravelu et al. 2018).
Spatial and temporal correlation between physicochemical parameters and ciliate diversity indices
Pearson correlation coefficients were calculated to determine the correlation between physicochemical parameters and species diversity, richness and evenness (Table 4). Ciliate species diversity calculated by the Shannon index (H') was found to be positively correlated with temperature (inside water), the concentration of phosphate, nitrite, nitrate and ammonia, whereas it was negatively correlated with pH, DO, TDS, EC, WH, concentration of chloride and sulphate. Ciliate species richness calculated by the Margalef’s index (d) was found to be positively correlated with EC, concentration of phosphate, nitrite, nitrate and ammonia whereas it was negatively correlated with TIW, pH, DO, TDS, WH, concentration of chloride and sulphate. Ciliate species evenness calculated by the Pielou’s index (J') was observed to be positively correlated with the concentration of phosphate, nitrate and ammonia, whereas it was negatively correlated with TIW, pH, DO, TDS, EC, WH and concentration of chloride, sulphate, and nitrite.
Table 4
Correlation between physicochemical parameters and species diversity, richness and evenness from three sites sampled for one year from September 2018 to August 2019.
Physicochemical parameters | Pearson correlation coefficients |
With species diversity (H') | With species richness (d) | With species evenness (J') |
Temperature (inside water) | 0.111 | -0.036 | -0.093 |
pH | -0.571* | -0.536* | -0.494* |
Dissolved Oxygen | -0.170 | -0.344 | -0.202 |
Total dissolved solids | -0.432 | -0.525* | -0.430 |
Electrical conductivity | -0.475* | 0.558* | -0.411 |
Water hardness | -0.284 | -0.245 | -0.095 |
Chloride | -0.463 | -0.573* | -0.496* |
Sulphate | -0.137 | -0.214 | -0.080 |
Phosphate | 0.458 | 0.436 | 0.378 |
Nitrite | 0.049 | 0.007 | -0.075 |
Nitrate | 0.158 | 0.104 | 0.072 |
Ammonia | 0.696** | 0.593** | 0.653** |
*Correlation is significant at p < 0.05 level and **correlation is significant at p < 0.01 level. |
Environmental changes have a significant correlation with the ciliate communities in the aquatic environments. Because of their small size and life span, they can resist or adapt to the environmental changes and therefore, the community is shaped according to the environmental conditions (Abdullah et al. 2018; Curds 1992). The environmental factors such as temperature, light, nutrients, salt concentration, food resources are major driving forces in establishing a community structure and slight changes in these variables can cause changes in the community composition of ciliates (Abdullah et al. 2018; Jiang et al. 2011; Sikder et al. 2019; Xu et al. 2014).
Temperature showed a positive correlation with the number of ciliates. The ciliate diversity represented by Shannon index (H') was relatively high in all the three sites in the post-monsoon months, i.e., September and November 2018 (Table 3 and Fig. 4). Similarly, species richness represented by Margalef’s index (d) was highest in September and November 2018 in all the three sites. The temperature ranged from 22–29°C during these months. This temperature range was observed to be desirable for the ciliate growth as reported in the previous studies (Babu et al. 2013; Bera et al. 2014; Kedar et al. 2008; Vajravelu et al. 2018). Pielou’ s evenness index was highest in September (0.48 ± 0.05) and November 2018 (0.53 ± 0.06) in case of OBS, highest in November 2018 (0.38 ± 0.10) and July 2019 (0.37 ± 0.06) in case of SL and in case of RJ it was highest in January 2019 (0.32 ± 0.08) and March 2019 (0.32 ± 0.04). A slight drop in the ciliate diversity, ciliate richness and ciliate evenness was observed in May 2019 (summer season) and July 2019 (monsoon season) where the temperature ranged from 30–35°C in all the sites. Similarly, in January 2019 (winter season), low ciliate diversity (H'=1.76 ± 0.43 in OBS and H'=0.18 ± 0.32 in SL), ciliate richness (d = 2.07 ± 0.98 in OBS and d = 0.12 ± 0.20 in SL) and ciliate evenness (J'=0.46 ± 0.07 in OBS and J'=0.06 ± 0.11 in SL) was observed in OBS and SL as the temperature was low ranging from 14–16°C. But, species evenness was observed to be high in case of RJ (J'=0.32 ± 0.08) during the winter season, i.e. in January 2019. It has been previously reported that evenness may increase at low temperature if the sample contains more taxonomically distinct species (Passy et al. 2016). Previous reports suggest that the temperature, within the desirable range (20 to 31°C), shows a positive correlation with species abundance (García et al. 2018; Limberger et al. 2014: Luna-Pabello et al. 1992). A temperature within this range helps in increasing the metabolism of the species thereby increasing the population density (Parain et al., 2019). The present study as well as the previous reports show that extremely high and low temperatures have a negative impact on the growth and replenishment of ciliates in the freshwater bodies (García et al. 2018; Limberger et al. 2014: Luna-Pabello et al. 1992).
pH correlated negatively with ciliate diversity, richness and evenness. High ciliate diversity, richness and evenness were observed during the post-monsoon season, i.e., September 2018 in all the sites with the pH in the range of 7.7–7.8. In OBS, the ciliate diversity was recorded to be lowest in May (summer) with a pH of 7.77 ± 0.08. In SL, the diversity was lowest in January (winter) with a pH of 7.7 ± 0.04 and in RJ, the lowest diversity was noticed in July (monsoon season) with pH of 8 ± 0.06. Thus, this indicates that increase in pH (from neutral to slightly alkaline) decreased the ciliate diversity since it has been reported that increase in pH or alkalinity decreases the growth of ciliate species (Abraham et al. 2019). On the other hand, extremely low pH creates an acidic environment which also negatively impacts the species diversity (Thirunavukkarasu et al. 2014; Vajravelu et al. 2018). The pH of freshwater bodies has been reported to decrease during autumn or monsoon seasons (Salim et al. 2015). This has been well correlated in the present investigation as well. Increase in pH indicates an increase of CO2 uptake by phytoplanktons leading to algal blooms (Thirunavukkarasu et al. 2014; Vajravelu et al. 2018). This gradually depletes the nutrient contents in the ecosystem thereby affecting the species diversity at higher pH (Abraham et al. 2019).
Dissolved oxygen (DO) content showed a negative correlation with the ciliate diversity, richness and evenness when compared among sites. There was no significant difference in the overall mean and range of DO values of all the three sites, with slightly low value in OBS (3.4 ± 1.55 mg/L), followed by SL (4.25 ± 1.66 mg/L) and comparatively high in case of RJ (5.45 ± 0.82 mg/L). Seasonal data suggests that in OBS, low DO was observed in September 2018 (2.5 ± 0.5 mg/L; postmonsoon), January 2019 (2.5 ± 0 mg/L; winter) and July 2019 (2 ± 1 mg/L; monsoon) and was high in May 2019 (6.3 ± 0.28mg/L; summer). In SL, the lowest DO was observed in January 2019 (2 ± 0.5 mg/L; winter) and highest DO was observed in September 2018 (7 ± 1.32 mg/L; post-monsoon). In RJ, lowest DO was observed in January 2019 (4.8 ± 0.28 mg/L; winter) and July 2019 (4.83 ± 0.28 mg/L; monsoon) and highest DO was observed in May 2019 (6.66 ± 0.57 mg/L; summer). Overall, DO was low in the post-monsoon and winter months and was high during summer months. In all the sites and all the months, the threshold value of dissolved oxygen was higher than the classic definitions of hypoxia (< 2.0 mg/L), suggesting favourable conditions for microbial growth (Spietz et al. 2015). The previous report on the DO levels of OBS suggests a low level of DO (average value of 1.6 ± 0.84 mg/L) in the year 2009–2010 (Manral and Khudsar 2013). DO levels have been reported to be low during the winter season due to low species diversity (Araoye 2007, 2009). Another study reported high DO levels in the monsoon season (Babu et al. 2013). This correlates with the present study where DO was low in all the sites during winter and high DO was observed in monsoon and summer season. The desirable DO concentration results in the availability of more oxygen to the organism thereby increasing species metabolism which positively influences the species diversity (Rajagopal et al. 2010).
Total dissolved solids (TDS) represent dissolved materials including inorganic salts and organic matter as well as toxic contaminants from industrial effluents, waste materials etc. present in the water body (Jayakumar et al. 2009; Weber-Scannell and Duffy 2007). The present study indicated a negative correlation between ciliate diversity, richness and evenness and TDS concentration. Among the three freshwater sites, the total mean value of TDS from all the months showed that OBS had the lowest TDS concentration (316.80 ± 31.26 mg/L), followed by SL (438.65 ± 145.30 mg/L) and RJ (939.81 ± 293.84 mg/L). Ciliate diversity was also maximum in OBS (H'=1.63–2.21), followed by SL (H'=0.18–1.64) and RJ (H'=0.50–1.33). Seasonal data suggests that in OBS lowest TDS was observed in January 2019 (272 ± 2.64 mg/L; winter) and highest TDS was observed in May 2019 (353 ± 2.64 mg/L; summer). In SL, the lowest TDS was observed in January 2019 (308 ± 0.57 mg/L; winter) and highest TDS was observed in July 2019 (663 ± 2 mg/L; monsoon). In RJ, lowest TDS was observed in September 2018 (573.33 ± 2.08 mg/L; post-monsoon) and highest in May 2019 (1362.3 ± 2.51 mg/L; summer). Overall seasonal data suggests that the lowest TDS was observed in winter and highest in summer. TDS correlates negatively with the species diversity, richness and evenness as it induces toxicity by increasing salinity in the water (Ivanova and Kazantseva 2006; Weber-Scannell and Duffy 2007). Thus, a high amount of TDS indicates poor quality of water and is directly proportional to the degree of water pollution (Bharati and Krishnamoorthy 1990; Tripathy and Adhikary 1990). The present study suggests that high concentration of TDS in a water body inhibits the growth and enrichment of ciliates.
Electrical conductivity (EC), similar to pH and TDS, correlates negatively with ciliate diversity, richness and evenness. OBS, having high ciliate diversity, showed the lowest EC mean value (600.90 ± 60.70 µS/cm) followed by SL (793.93 ± 135.86 µS/cm) and highest was in RJ (1361.70 ± 281.25 µS/cm). It has been reported that high EC indicates the hypersaline condition of the water which inhibits ciliate diversity (Abraham et al. 2019). EC is considered to be an important factor for characterizing water quality (Esteves 1988). High EC content in water suggests that there may be an increased sewage load and/or industrial effluents in the freshwater bodies thereby increasing water pollution level (Dias et al. 2008). High EC content in the RJ pond may be due to effluents from the adjacent sewage treatment plants and thermal power station.
Water hardness (WH) also correlated negatively with the ciliate diversity, richness and evenness in the present study. OBS having highest ciliate diversity, richness and evenness showed the lowest value of WH (132.11 ± 68.99), followed by SL (134.38 ± 83.23), and highest was observed in RJ (307.5 ± 194.87). WH was observed to be lowest in July 2019 (monsoon season) which favoured ciliate diversity and WH was highest in November 2018 and March 2019 where ciliate diversity was comparatively low. WH represents the presence of dissolved minerals such as inorganic salt contents (calcium and magnesium) in water. WH generally remains high in summers than in monsoon or winter season as high-temperature increases solubility of calcium and magnesium in water (Vyas and Sawant 2008). This correlates with the present study since WH is maximum during March and lowest in monsoon season. High WH again signifies more alkaline water which lowers species diversity (Boyd et al. 2016). In the present study, chloride and sulphate showed a negative correlation with the ciliate diversity, richness and evenness where OBS (with high ciliate diversity) had lowest mean value of the chloride concentration (69.90 ± 27.15 mg/L) and sulphate (86.63 ± 11.54 mg/L), followed by SL (119.95 ± 62.84 mg/L of chloride and 98.95 ± 41.70 mg/L of sulphate) and RJ (283.12 ± 107.29 mg/L of chloride and 181.66 ± 99.62 mg/L of sulphate). Seasonal data of chloride and sulphate provide no significant correlation with species diversity, richness and evenness and it varied according to dynamics of different sites. In OBS, chloride was lowest in September 2018 (43.4 ± 1.5 mg/L; winter) and highest in July 2019 (111.8 ± 0.81 mg/L; monsoon); sulphate was lowest in January 2019 (77.7 ± 7.01 mg/L; winter) and highest in November 2018 (106 ± 1.76 mg/L; winter). In SL, chloride was lowest in September 2018 (60.1 ± 0.36 mg/L; post-monsoon) and highest in July 2019 (221.9 ± 0.59 mg/L; summer); sulphate was lowest in March 2019 (49.7 ± 5.55 mg/L; spring) and highest in July 2019 (176.3 ± 11.84 mg/L; monsoon). In RJ, chloride was lowest in September 2018 (149.21 ± 0.55 mg/L; post-monsoon) and highest in May 2019 (445.22 ± 2.38 mg/L; summer); sulphate was lowest in July 2019 (103.8 ± 10.42 mg/L; monsoon) and highest in March 2019 (373.7 ± 10.59 mg/L; spring). Nutrients such as chloride and sulphate have been reported to show a negative correlation with species diversity (Mohan et al. 2013; Rath et al. 2016). Chloride and sulphate salts are known to affect microorganisms at higher concentration since the presence of these salts increases water salinity (Rath et al. 2016). These soluble salts lower the microbial activity as they induce osmotic stress (Rath et al. 2016). This affects the nutrient intake of these microorganisms and makes them permissible to toxic soluble salts (Greaves 1992; Yan et al. 2015). Chloride and sulphate are known to enter the cells and disrupts the proper functioning of the microorganisms by interfering with their key enzyme activity (Greaves 1992; Rath et al. 2016). Also, chloride is reported to be more toxic than sulphate since it is known to inhibit protein synthesis by interfering with the binding of ribosomes to mRNA (Choquet et al. 1989; Rath et al. 2016; Weber et al. 1977).
The present investigation showed a positive correlation between ciliate diversity and phosphate, nitrite, nitrate and ammonia. Among the three freshwater sites, OBS, which had highest ciliate diversity, showed a significantly high concentration of phosphate (0.87 ± 0.92 mg/L) and ammonia (9.16 ± 2.04 mg/L) as compared to SL (0.43 ± 0.67 mg/L of phosphate and 2.02 ± 2.31 mg/L of ammonia) and RJ (0.49 ± 0.73 mg/L of phosphate and 0.45 ± 0.102 mg/L of ammonia). In all the sites, phosphate was highest in September 2018 (post-monsoon) and November 2018 (autumn) and ammonia was low in September 2018. Nitrite and nitrate showed no specific pattern seasonally it varied according to the dynamics of the site. Phosphate and inorganic nitrogen (nitrite, nitrate and ammonia) are known to correlate positively with species diversity by increasing ciliate biomass since they act as nutrients and help in the growth of microorganisms (Dopheide et al. 2009; Wang et al. 2014). Phosphate and inorganic nitrogen have been reported to directly favour the growth of photosynthetic ciliates and indirectly favour the growth of heterotrophic ciliates (Wang et al. 2014). The inorganic nitrogen parameters (nitrite, nitrate and ammonia) are generally present in abundance in areas having nitrifying bacteria which act as primary feeders for ciliates (Prast et al. 2007).
Physicochemical and ciliate diversity data for all the seasons and all the sites were combined and plotted using nonmetric multidimensional scaling (NMDS) (Fig. 5). The plot and the distance values suggest that the physicochemical parameters and diversity data estimated for September 2018 are distinct from the other months, hence lies separated at the upper right quadrant of the plot. May 2019 and July 2019 lie at the lower right quadrant of the plot. January 2019 and November 2019 lie at the lower left quadrant. March 2019 lies separately at the lower left quadrant. The distance values also suggest that the characteristics of September 2018 were distinct from the other months.
Physicochemical and ciliate diversity data for all the sites studied for different months were combined and plotted using nonmetric multidimensional scaling (NMDS)
(Fig. 6). The three sites OBS, SL and RJ were placed separately in different quadrants on the plot. The distances of sites with each other suggest that the physicochemical parameters and ciliate diversity data of OBS were closely related to SL than with the RJ. SL and RJ were more closely related to each other than with OBS.
Ciliate community composition varied in each site and during different seasons. A total of 44 species belonging to 8 classes from OBS, 18 species belonging to 6 classes from SL, and 13 species belonging to 6 classes from RJ were identified from September 2018 to August 2019 (Table 5). Percent relative abundance (RA%) of each species belonging to different classes identified in each month for all the three sites were calculated and summarized in Figs. 7–9.
In OBS, species with maximum relative abundance belonged to the class Spirotrichea (47%) followed by class Oligohymenophorea (20%), Prostomatea (16%), Phyllopharyngea (6%), Colpodea (5%), Heterotrichea (3%), Litostomatea (2%) and Karyorelictea (1%). In SL, species with maximum relative abundance belonged to the class Prostomatea (38%), followed by Spirotrichea (23%), Oligohymenophorea (21%), Colpodea (7%), Phyllopharyngea (6%), Litostomatea (5%). In RJ, species with maximum relative abundance belonged to the class Spirotrichea (38%), followed by Prostomatea (37%), Oligohymenophorea (17%), Phyllopharyngea (5%), Heterotrichea (2%), and Colpodea (1%) (Fig. 10).
In the present study, significant temporal variations in the ciliate composition was observed i.e. some ciliates were observed throughout the year and some were observed only once or twice in the year. Their temporal variations were analysed based on the number of species and their percent relative abundance for each site and each month (Figs. 7–9). Total abundance corresponds to the approximate number of individuals observed per ml which was calculated for each site for each month and summarised in Fig. 11. In OBS, the highest number of species were observed in September 2018 (29 species), followed by November 2018 (23 species), July 2019 (18 species), January 2019 (15 species), March 2019 (12 species), and May 2019 (10 species). Species that were observed in all the months (6 out of 6 months) were from the genera Aponotohymena, Tetmemena and Paramecium. Species observed in 5 out of 6 months sampled belonged to the genera Oxytricha, Gonostomum, and Coleps. In SL, the highest number of species were observed in September 2018 (11 species), followed by March 2019 (9 species), November 2018 (5 species), July 2019 (5 species), May 2019 (4 species), and January 2019 (3 species). Some species that were observed in most of the sampled months i.e. 6 out of 6 months was Coleps, Tetmemena (5 out of 6 months) and Gonostomum (4 out of 6 months). In RJ, the highest number of species was observed in September 2018 (7 species), followed by March 2019 (6 species), November 2018 (5 species), January 2019 (5 species), July 2019 (5 species) and May 2019 (4 species). Species that were observed in most of the months were members of the genera Coleps (6 out of 6 months). Gonostomum (4 out of 6 months), and Paramecium (4 out of 6 months). In all the three sites, the total number of species showed a peak in September 2018 and there was a significant drop in January 2019 and May 2019. Abundance was observed to be highest in September 2018 and lowest in January 2019 (Fig. 11).
This study evidently shows that ciliate diversity and composition depends on season as well as dynamics of each site. Also, the major contributors to the community structure were ciliates belonging to the classes Spirotrichea, Oligohymenophorea, and Prostomatea which were predominantly present in the monsoon (July 2019) and post-monsoon seasons (September 2018 and November 2018). The ciliates of these classes were comparatively low in the summer (May 2019) and winter (January 2019) seasons in all the three sites. The present study is similar to the previous reports which indicated that the ciliate abundance was low in the summer and winter seasons (Sikder and Xu 2020; Zhang and Xu 2015; Zhang et al. 2013). This could be due to the extreme water temperature and/or inadequate food supply (Sikder and Xu 2020). Class Spirotrichea was predominantly observed in all the three sampling sites which is similar to other reported studies from Delhi (Kaur et al. 2021), Tamil Nadu (Basuri et al. 2020), Tunisia (Dhib et al. 2013), and the Yellow Sea, China (Sikder and Xu 2020). OBS site had the highest percentage of spirotrich ciliates as compared to the other two sites. Spirotrich ciliates, especially urostylid group was observed only in OBS. Growth of Spirotrich ciliates including urostylids is generally encouraged in sites enriched with nutrients such as phosphate and inorganic nitrogen contents (Basuri et al. 2020; Dhib et al. 2013). Since OBS site had high concentration of phosphate (0.87 ± 0.92 mg/L) and ammonia (9.16 ± 2.04 mg/L), that could be related to high percent of spirotrich ciliates.