Phytoplankton diversity and biomass production ...

ISSN 2449-8866

Current Life Sciences

Research Article

Phytoplankton diversity and biomass production under changing weather variables B. Elayaraj1*, S. Dhanam2, K. V. Ajayan3, M. Selvaraju1 1

Environmental Science Division, Department of Botany, Annamalai University, Annamalai Nagar - 608 002, Tamil Nadu, India 2 Department of Botany, Arignar Anna Government Arts College, Villupuram - 605 602, Tamil Nadu, India 3 Environmental Science Division, Department of Botany, University of Calicut, Kerala, India *Corresponding author: B. Elayaraj; E-mail: [email protected]

Received: 14 August 2016; Revised submission: 27 September 2016; Accepted: 12 October 2016 Copyright: © The Author(s) 2016. Current Life Sciences © T.M.Karpiński 2016. This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

ABSTRACT

1. INTRODUCTION

Relation between phytoplankton composition and weather variables were studied in a shallow pond at Chidambaram taluk of Tamil Nadu. Seasonal differences in the quantitative and qualitative composition were analyzed. The pond water was sampled in the period from January to December 2015. In order to assess the phytoplankton diversity, biomass production and abundance were measured along with nutrient concentrations. Results showed an increased concentration in physico-chemical parameters and phytoplankton density during summer season followed by premonsoon and monsoon season. Over 62 species of phytoplankton represented by 22 species of Cyanophyceae, 17 species of Chlorophyceae, 15 species of Bacillariophyceae and 8 species of Euglenophyceae were recorded. The results of the present study indicated that the water of the pond lies below the level of eutrophication.

Phytoplankton plays an important role in aquatic ecosystems as they produce oxygen and food, which sustain all other forms of life, ensuring ecological balance [1]. With a global carbon fixation of about 50Gt carbon per annum the marine species contribute nearly 50% to the total primary production of Earth [2]. Phytoplankton primary production is the major bottleneck through which solar energy enters the marine and freshwater food webs [3]. Until today it is used as a major descriptor of the trophic state of lakes [4]. The biota of an aquatic ecosystem comprises micro-/macrofauna, besides a wide range of organisms including micro-/macrophytes. Phytoplankton present in wastewater systems can be used as indicators of water pollution [5], as they are the primary producers and have a key role in biotic and abiotic interactions of aquatic systems and possess the ability to survive in oligotrophic to eutrophic environments. They also play a role in nutrient sequestration and removal of other contaminants from wastewaters. Studies on microalgal diversity and their associations in the water bodies as biological indicators are helpful in the assessment of water quality [6]. Studies concerning algae for

Keywords: Phytoplankton; Diversity; Weather; Eutrophication.

Current Life Sciences 2016; 2 (4): 102-113

103 | Elayaraj et al. Phytoplankton diversity and biomass production under changing weather variables

monitoring water quality show that changes in phytoplankton composition reflect not only variation in water quality, but also changes in physical and chemical variables and biotic interactions. This implies the importance of biomonitoring studies in a variety of aquatic ecosystems. Ecological studies include seasonality of phytoplankton and variation of physico-chemical factors in water bodies and evaluate the relationship between algal taxa and environmental factors [6, 7]. The quality and quantity of phytoplankton and their seasonal patterns have been successfully utilized to assess the quality of water and its capacity to sustain heterotrophic communities [8]. Nutrient composition of water bodies also determines the phytoplankton community structure. Imbalance in the nutrient ratio (N:P) can lead to the growth of certain allelochemical producing species, which suppresses the growth of other organisms [9]. Water quality affects the abundance, species composition, productivity and physiology of these organisms [10]. Therefore, it is important to study the frequent analysis of phytoplankton variation in response to environmental changes. Thus, in the present study; phytoplankton succession had been examined periodically from January to December 2015 in the Sri Kamatchiamman temple pond to evaluate the relationships between phytoplankton compositions, abundance and biomass with environmental factors.

1m. The collected samples were preserved in 1 litre polyethylene bottles for detailed laboratory analysis. Water temperature was measured using a digital thermometer from field itself. Total solids were determined in accordance with the method outlined by APHA [11]. A known quantity (25 ml) of a wellmixed sample was filtered through a pre-weighed Whatman GF/C filter with a pore size of ~0.45 µm. The filters were then dried at 105 °C, cooled in desiccators and weighed. The cycle of drying, cooling, desiccating, and weighing was repeated to ensure constant weight was obtained. Turbidity was measured using a laboratory nephelometer (Elico Model CL 52D) and was expressed in NTU (Nephelometric turbidity units). A standard reference turbidity tube of 79 NTU was used at each time of operation as an additional measure of turbidity. Electrical conductivity is measured with the help of a conductivity meter (Elico Model CM 183). Total alkalinity, BOD, COD and all nutrients were determined using Hach reagents according to Hach protocols and standard methods [11].

2. MATERIALS AND METHODS 2.1. Study area

Figure 1. Water sample site is shown in the map with geographical position.

The Sri Kamatchiamman temple pond (SKT pond) is located in Chidambaram taluk nearby Kavarappattu village (Fig. 1). It is situated at 11º 22' N latitude and 79º 44' E longitude at an elevation of 7.00 m above the msl. The water sample has been collected in the morning between 9.00 am to 11.00 am regularly at monthly intervals (Six sample from different site of the same pond), over a period of one year (January to December 2015). 2.2. Water sample analysis The water samples were collected using integrated water sampler from the surface depth of

2.3. Phytoplankton determinations Phytoplankton samples were collected by towing a plankton net made of bolting silk (mesh aperture size: 25 µm) for half an hour on the surface of the water at the sampling site at different seasons. These samples were preserved in 4% neutralized formalin and used for further analysis. The volume of water filtered was calculated by using the formula V = r2dπ, where V = volume of water filtered, r = radius at the mouth of the net, d=distance through which net was towed. Quantitative analysis



of phytoplankton was done using a haemocytometer and a Nikon Eclipse Microscope (Nikon Eclipse Model 200) following the procedure of Martinez et al. [12]. Phytoplankton was identified under a compound light microscope using keys and illustrations by Stafford [13] and Prescott [14] and other phycological taxonomic books. 2.4. Phytoplankton biomass Chlorophyll ‘a’ is determined by spectrophotometer by using this formula [15]:  µg   Extract Vol. (ml )   = (11.6 × OD 664 − 1.31 × OD 647 − 0.14 × OD 630 )   Chl ' a '   10 ml   Cuvette width (cm ) 

2.5. Statistical analysis The statistical analyses were performed using the software Statistical Package for Social Sciences (SPSS Version 21). Correlation coefficients were calculated using Microsoft Excel package and analyzed for their significance using Pearson's tables. 3. RESULTS 3.1. Environmental variations Environmental parameters are considered as one of the most important features that are capable of influencing the growth, abundance and diversity of phytoplankton in the pond and are showed wide temporal and spatial differences. Variations in physico-chemical parameters of the surface pond water are given in Table 1. Pond water temperature (WT) recorded at different seasons ranged from 27.4 to 36.8 °C. The minimum WT was observed during monsoon season and the maximum was registered during summer season. The maximum (59.1 NTU; 139.0 mg/l) and minimum (31.7 NTU; 113.0 mg/l) turbidity and total solids was registered during summer and monsoon seasons. The highest electrical conductivity was found during monsoon (788.9 µS) and the least value was found in summer (619.5 µS). The pH was always alkaline in each season and fluctuated between 7.67 (monsoon) and 9.09 (summer). The lowest (81.2 mg/l) total alkalinity was noticed during monsoon as the rain water dilutes its concentration and highest (103.2

mg/l) during summer when the water was minimum in the pond. The DO concentration varied between 6.01 mg/l and 7.65 mg/l, registering minimum and maximum values during summer and monsoon seasons. The BOD was maximum (4.68 mg/l) during summer and minimum (2.57 mg/l) during post monsoon. COD of the sample was high (7.84 mg/l) during post monsoon and low (5.58 mg/l) during pre monsoon. 3.2. Nutrients Five nutrients viz., calcium, magnesium, chloride, phosphate and nitrate were estimated in water samples during the investigation. Concentration of calcium, magnesium and chloride varied from 36.2 mg/l to 26.61 mg/l; 15.8 to 9.48 mg/l and 70.88 to 59.64 mg/l respectively. The highest amount of calcium and magnesium was seen during summer and lowest amount was recorded during monsoon. The peak amount of chloride is seen in summer and lowly during post monsoon season. The maximum inorganic phosphate content was recorded (2.26 mg/l) during summer season and minimum (1.8 mg/l) in monsoon season. The nitrate concentration was quite high throughout the study period ranging from 2.78 to 3.27 mg/l with the minimum (summer and monsoon) and maximum (post monsoon) season at pond water respectively. 3.3. Phytoplankton composition, abundance and biomass A total number of 62 species were identified in the phytoplankton community, during the study (Table 2). The phytoplankton was represented by four main groups namely; Cyanophyceae, Chlorophyceae, Bacillariophyceae and Euglenophyceae. The species present in different groups were Cyanophyceae (22 species), Chlorophyceae (17 species), Bacillariophyceae (15 species), and Euglenophyceae (8 species). The highest diversity and density were observed during summer and lowest in monsoon period (Graph 1). Cyanophyceae was relatively abundant as compared to all other groups, which accounted for 37% of phytoplankton followed by Chlorophyceae with 28%, Bacillariophyceae with 24% and Euglenophyceae consisted of 11%.



S. No 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.

Table 1. Seasonal variations of ecological variations of Sri Kamatchiamman Temple Pond – 2015. Post-monsoon Summer Pre-monsoon Physico-chemical parameters Jan Feb Mar Apr May Jun Jul Aug Sep Temperature (º C) 27.6 28.4 30.9 34.2 33.0 36.8 33.2 32.0 30.7 Turbidity (NTU) 57.2 52.5 56.0 53.7 59.1 54.9 49.4 54.7 49.5 Electrical 745.6 742.3 698.0 663.8 619.5 634.3 657.2 692.8 703.1 conductivity (µS) Total solids (mg/l) 115 121 124 119 113 116 122 127 123 pH 7.89 7.94 7.92 9.09 8.94 8.77 8.39 8.24 8.09 Total alkalinity 83.4 85.9 90.1 100.4 103.2 102.9 100.7 95.6 92.3 (mg/l) Dissolved oxygen 6.91 6.65 6.29 6.33 6.12 6.01 6.2 6.34 6.86 (mg/l) Biological Oxygen 2.57 2.70 3.88 3.96 4.52 4.68 4.31 4.16 4.02 Demand (mg/l) Chemical Oxygen 7.61 7.84 5.85 6.06 5.73 5.69 5.92 5.58 5.99 Demand (mg/l) Calcium (mg/l) 29.53 31.18 31.22 35.27 36.2 32.49 32.08 30.3 29.7 Magnesium (mg/l) 12.47 11.89 12.92 13.75 15.8 14.0 14.54 12.72 12.36 Chloride (mg/l) 61.3 59.64 62.87 67.0 70.12 70.88 68.9 65.18 64.75 Phosphate (mg/l) 1.93 1.99 2.04 2.01 2.1 2.26 2.13 2.05 1.99 Nitrate (mg/l) 3.27 3.15 3.11 2.85 2.78 2.82 3.07 3.02 2.94

Table 2. Microalgal distribution in the water sample of SKT Pond – 2015. S. Name of the species No. J F M Cyanophyceae 01 Microcystis aeruginosa Kütz. + + + 02 Microcystis flos-aquae (Wittr.) Kirchner + + + 03 Aphanocapsa pulchra (Kütz.) Rabenh 04 Merismopedia punctata (Meyen) + + 05 Aphanotheceae microscopica Naegli + + 06 Chroococcus turgidus (Kütz.) Naegli + 07 Aphanocapsa littroralis Hansgirg 08 Chroococcus minor (Kütz.) Nageli + + 09 Lyngbya shackletoli West + + + 10 Oscillatoria curviceps Ag. ex Gomont + + 11 Oscillatoria subbrevis Schmidle F. Crassa + + 12 Spirulina major (Kütz.) Gomont + + + 13 Spirulina princeps Voucher ex. Gomont + + + 14 Anabaena spiroides Klebahn + + + 15 Nostoc pruniforme Ag. + + + 16 Oscilltoria tenuis Ag. Ex Gomont + + + 17 Merismopedia minima Beck + 18 Gomphosohaeria aponina (Kütz.) + + 19 Merismopedia elegans G.M. Smith 20 Merismopedia glauca (Ehr.) Nageli + 21 Aphanocapsa grevillei (Hass.) Rabenh + + +

Monsoon Oct Nov 31.1 28.9 48.2 31.7

Dec 27.4 34.1

681.8

758.4

788.9

132 7.67

134 7.96

139 7.99

85.6

81.2

82.8

6.61

7.65

7.3

3.78

2.83

2.97

6.76

6.68

6.8

32.16 10.53 61.1 1.91 2.78

28.4 10.21 63.71 1.8 2.92

26.61 9.48 68.78 1.86 2.95

A

Months – 2015 M J J A

S

O

N

D

+ + + + + + + + + + + + + + + + + + + +

+ + + + + + + + + + + + + + + + + + + + +

+ + + + + + + + + + + + + + + +

+ + + + + + + + + + + + -

+ + + + + + + + + + + -

+ + + + + + + + + + +


+ + + + + + + + + + + + + + + + + + + + +

+ + + + + + + + + + + + + + + + + +

+ + + + + + + + + + + + + + + + + + -


S. No. 22

Name of the species

J +

F +

M +

A -

Chroococcus disperses (V. Keissler) Lemm. Chlorophyceae 23 Chlamydomonas globosa Snow. + + + + 24 Tetraspora lubrica (Roth) Ag. + + + 25 Palmella miniata Lieb. + + + 26 Scenedesmus bijiuga (Reinsch) + + + + 27 Westella botryoides (W. West) + + 28 Chlorella pyrenoidosa Chick + + + + 29 Chlorella vulgaris Beyernick + + + + 30 Pediastrum biradiatum Presc + + 31 Chlorosarcina consociate (Klebs) G.M. Smith + 32 Scenedesmus accuminatus Kütz. + + + + 33 Scenedesmus quadricauda (Turp.) Breb. + + + + 34 Cladophora crispate (Roth) Kütz. 35 Pediastrum duplex Meyen + 36 Spirogyra sps. + + + + 37 Closterium purvulum Nageli + + + 38 Selenastrum biraianum Reinsch + + 39 Eudorina elegans Ehr. + Bacillariophyceae or Diatoms 40 Pinnularia gibba Ehr. + 41 Skeletonema costatum (Grev.) Cleve. + + 42 Thalassiosira marginata Sp. Nov. 43 Anomoeneis sphoerophora (Kütz.) + + + + 44 Calonies silicula (Ehr.) Cleve 45 Cyclotella meneghiniana Kütz. + + + + 46 Diploneis subovalis Cleve + + + 47 Cymbella alpina Grun + 48 Amphora ovalis Kütz. + + + 49 Diatoma sps. + + + + 50 Navicula cincta Kütz. 51 Diploneis interrupta (Kütz. + + 52 Eunotia monodon Her. + + + + 53 Pinnularia braunii Grun. + 54 Navicula peregrine Kütz. + + + + Euglenophyceae 55 Euglena viridis Ehr. + + + + 56 Euglena convolute Korsch + + + 57 Euglena polymorpha P.A.Dange. + + 58 Euglena spirosura var. Fusca + + + + 59 Euglena viridis O.F. Mullers 60 Phacus pleuronectes Dujardin + + + 61 Euglena oxyuris fo. Maior + + + 62 Euglena elastic Presc. + + + (+) = Present, (-) = Absent, J-January, F-February, M-March, A-April, M-May, O-October, N-November, D-December.

Months – 2015 M J J A + + -

S -

O -

N +

D +

+ + + + + + -

+ + + + + + + + -

+ + + + + + + -

+ + + + + + + + + + + -

+ + + + + + + + + + + + -

+ + + + + + + + + + + + + + + +

+ + + + + + + + + + + + + + + + +

+ + + + + + + + + + + + + + + +

+ + + + + + + + + + + + +

+ + + + + + + + + + + -

+ + + + + + + + -

+ + + + + + + + + -

+ + + + + -

+ + + + + -

+ + + + + + + + + +

+ + + + + + + + +

+ + + + + + + + + + + + + + + + + + + + + + J-June, J-July,


+ + + + + + + + + + + A-August,

+ + + + + + + + + + S-September,


The number of individual species in different phytoplankton groups started to increase from the pre monsoon season and reached its maximum in the summer season. A total of 22 dominant species of Cyanophyceae were observed viz., Microcystis aeruginosa, Microcystis flos-aquae, Aphanocapsa pulchra, Merismopedia punctata, Aphanotheceae microscopic, Lyngbya shackletoli, Oscillatoria curviceps, Oscillatoria subbrevis, Spirulina major, Spirulina princeps, Anabaena spiroides, Nostoc pruniforme, Oscilltoria tenuis and Aphanocapsa grevillei Followed by Chlorophyceae viz., Chlamydomonas globosa, Tetraspora lubrica, Scenedesmus bijiuga, Chlorella pyrenoidosa, Chlorella vulgaris, Scenedesmus accuminatus, Scenedesmus quadriccauda, Spirogyra sp., and Closterium purvulum Bacillariophyceae viz., Pinnularia gibba, Cyclotella meneghiniana, Diploneis subovalis, Cymbella alpine and Diatoma sp., and Euglenophyceae viz., Euglena viridis.

Graph 1. Seasonal variations of Biomass or Chlorophyll ‘a’ content of SKT Pond - 2015.

Graph 2. Percentage of Microalgae groups of SKT Pond - 2015.

Euglena polymorpha, Euglena spirosura, Phacus pleuronectes and Euglena oxyuris. Chlorophyll ‘a’ concentrations ranged from 1.542 mg/l to 6.975 mg/l with the minimum in monsoon and maximum in summer (Graph 2). 3.4. Correlation coefficient The statistical analysis of Pearson’s correlation coefficient is presented in the Table 3. The water temperature was significantly positively correlated with turbidity, pH, total alkalinity, BOD, calcium, magnesium and chloride of phytoplankton community. On the other hand, water temperature showed strict negative correlation with electrical conductivity, total solids, dissolved oxygen, COD, phosphate and nitrate in water body. Turbidity showed significant positive correlation with pH, total alkalinity, BOD, calcium, magnesium and nitrate of phytoplankton community and significant negative correlation with electrical conductivity, total solids, dissolved oxygen, COD, chloride and phosphate content in water. The electrical conductivity showed significant positive correlation with total solids, dissolved oxygen, COD, phosphate and nitrate of phytoplankton community and significant negative correlation with pH, total alkalinity, BOD, calcium, magnesium and chloride content in water. Total solids have positive correlation with dissolved oxygen, COD and potassium in the pond. But it has negative correlation with pH, total alkalinity, BOD, calcium, magnesium, chloride and nitrate content. The pH showed significant positive correlation with total alkalinity, BOD, calcium, magnesium and chloride. But pH has negative correlation with dissolved oxygen, COD, phosphate and nitrate. Total alkalinity positive correlation with BOD, calcium, magnesium and chloride in the pond. But it has negative correlation with dissolved oxygen, COD, phosphate and nitrate content. Dissolved oxygen has positive correlation with COD, phosphate and nitrate and showed negative correlation with BOD, calcium, magnesium and chloride of phytoplankton community. The high level of BOD was decreased the phytoplankton community. However, it showed negative correlation with COD, phosphate and nitrate content. The COD showed significant positive



correlation with phosphate and nitrate of phytoplankton community however, it showed negative correlation with calcium, magnesium and chloride content. Calcium was positively correlated with magnesium and chloride and negatively correlated with phosphate and nitrate in this study. Magnesium has positive correlation with chloride and on the other hand showed negative correlation with phosphate and nitrate content. The increase in magnesium content also increases the density of phytoplankton community. Chloride showed significant positive correlation with phosphate of phytoplankton community and significant negative correlation with nitrate content in water. Increasing phosphate in the pond also increases nitrate content as well as density of phytoplankton community. Phosphate has negative correlation with nitrate content. The result also revealed that nitrate was highly responsible for significantly reduction in density of phytoplankton community in the pond.

Chlorophyll ‘a’ is positively correlated with temperature, turbidity, pH, total alkalinity, BOD, calcium, magnesium, chloride and negatively correlated with electrical conductivity, total solids, dissolved oxygen, COD, phosphate with nitrate in pond water. The distributions of certain phytoplankton community were almost positively correlated with temperature, turbidity, pH, total alkalinity, BOD, calcium, magnesium, chloride and chlorophyll ‘a’ content in water. However, it showed negative correlation with electrical conductivity, total solids, dissolved oxygen, COD, phosphate and nitrate content. Phytoplanktons have a positive correlation with temperature where maximum number of phytoplankton observed during summer season and minimum during the monsoon season. The higher pH, electrical conductivity, alkalinity, total solids, BOD and COD were observed in summer season similarly it also increased nitrate and phosphate contents during summer season.

Table 3. Correlation coefficient of physico-chemical parameters, chlorophyll ‘a’ and phytoplankton members of SKT Pond - 2015. Temp. Temp. Tur.

1

Tur.

EC

TS

.463 -.905**

TA

1 -.652* -.852**

.389

*

*

1

EC

pH

DO

BOD

COD

.634

.586* -.825**

-.707 -.907

**

.871

**

.464

-.239

**

*

-.903

TS

1 -.580* -.630*

.668*

-.373

pH

**

*

*

1 .868

TA

COD

Cl2

.675* .770**

.151 -.687* -.858**

-.173

.600*

Cl2

.155

.501

.406

*

**

-.893**

-.123 -.722** -.797** -.767**

-.503

-.436

**

.771**

.502 -.922

**

-.347

-.402 .932** .940**

.756

.559 -.775** -.830** **

*

.634

1

-.402

.747

**

-.883

**

1 -.847** .892** -.756** .768** .890** .711**

-.576 .733

Eug.

.489 .906** .865**

.672* .742** .806**

-.472 .779

.637

**

Chl a Cyan. Chlo. Bacil.

-.554 .834** .833**

-.171

-.586

**

.793

**

-.700 -.929

.550 .808

.674* .920** .935**

.165 -.824** -.902** -.805** -.785** -.753**

-.370

.437

*

-.309

-.561 .843** .786**

.505 .914** .927**

-.549 -.678*

.175

.502 -.724** -.623*

-.340 -.806** -.850**

.703

*

1

Mg

-.003 -.579* .546

-.846

1 .798**

Ca

NO3

-.417

-.509

.694 -.871

**

PO4

.628*

**

1 -.900

BOD

Mg

**

1 -.791**

DO

Ca

-.483 .765** .905** -.792** .898** -.759** .713** .708**

.655

.300

-.544

-.433 .776** .799** .820** .827**

.693* .806**

.288

-.516

.607*

.554

.174

1

-.044

-.506

-.468

-.499

-.407

-.281

1

-.317

-.186

-.031 -.619*

-.515

1 .927

Chl a

.724

**

.784

**

1

**

.863

**

-.522

NO3

.960

**

.491

PO4

-.093 .940

**

.619* .771**

.880

**

.919**

1 .838** .857** .842**

Cyan.

1

Chlo.

.667*

.588*

1 .924**

Bacil.

1

Eug.

** Correlation is significant at the 0.01 level (2-tailed), * Correlation is significant at the 0.05 level (2-tailed), Temp-Temperature, Tur-Turbidity, EC-Electrical conductivity, TS-Total solids, TA-Total solids, DO-Dissolved solids, BOD-Biological Oxygen Demand, COD-Chemical Oxygen Demand, Ca-Calcium, Mg-Magnesium, Cl2-Chloride, PO4-Phosphate, NO3-Nitrate, Chl a-Chlorophyll ‘a’, Cyan-Cyanophyceae, Chlo-Chlorophyceae, Bacil-Bacillariophyceae, Eug-Euglenophyceae.



4. DISCUSSION 4.1. Environmental variations The study revealed a wide variation in the physico-chemical characteristics and microalgal diversity of pond water during the study period. Estimating the water quality is very important in determining the quality of ecosystem [16]. Water temperature is an important parameter which influences the chemical process such as dissolutionprecipitation, adsorption-desorption, oxidation-reduction and physiology of biotic community in an aquatic habitat. Generally, water temperature (WT) has been influenced by the intensity of solar radiation, evaporation, freshwater influx and cooling and mix-up with ebb and flow from adjoining necrotic waters. The WT varied from 27.4 to 36.8°C mainly in line with changes in seasonal variations. Higher WT recorded during the summer season might be due to the increased solar radiation [17]. Though the WT is capable of altering the reproduction, growth, metabolism, microbial processes and especially photosynthesis rates, the observed ranges are not alarming and are within the optimal range (18.3 to 37.8 °C) for production of plankton in tropical waters [18, 19]. Turbidity is an important physical parameter which has a significant bearing on productivity of aquatic ecosystem [20]. The particulate matter like clay, silt, colloidal particles, algal blooms, debris and the other microscopic organisms are responsible for turbidity in water. Turbidity directly affects the productivity of surface water because scatter and absorption of light in water depends upon turbidity. Total solids in the nearly all of the cases are organic in nature and pose serious problems of pollution. Electrical conductivity of water is a numerical expression of the ability of water sample to carry an electric current. It depends on the nature and concentration of ionized substances or electrolytes dissolved in water. pH is known as the master variable in water since many properties, processes and reaction are pH dependent. pH is one of the major factors controlling the growth, establishment and the overall diversity of different groups. The pH (neutral-alkaline) is known to support faster growth and establishment of Cyanophyta, than that of other microalgal groups [21]. In the present investigation,

the predominance of Cyanophycean genera can be directly related to the neutral to alkaline pH (7.679.09) of sewage wastewater. The higher alkalinity in summer seasons may be attributed to the high rate of decomposition where CO2 was released and reacted with water to form HCO3 and thereby increasing the total alkalinity. Higher level of alkalinity was mainly due to the flow of agricultural runoff. Such observations coincide with the results of Ajagekar et al. [22]. Dissolved oxygen is an important constituent of water and its concentration in water is an indicator of prevailing water quality and ability of water body to support a well-balanced aquatic life. With the progression of monsoon, DO raised to its peak value, and it might be due to high rate of photosynthesis by phytoplankton population that forms the major source of DO [23]. The lowest DO concentration observed at the lower reaches might be because of the influence of salinity, temperature, conductivity, currents and upwelling tides [24]. BOD increases as the bio-degradable organic content increases in waters. Jena et al. [25] reported the same during summer at Sagal Island and Khanna and Singh [26] noticed peak values during summer in Suswa river of Dehradun. The high COD values indicate that some degree of non biodegradable oxygen demanding pollutants were present in the water. The values of COD in conjugation with BOD are helpful in knowing the toxic conditions and presence of biologically resist organic substances. These observations support the findings of Khanna and Singh [27] and Sharma [28]. 4.2. Nutrients Calcium is an important nutrient for aquatic organism and it is commonly present in all water bodies. Magnesium is found in various salt and minerals, frequently in association with iron compound. Magnesium is vital micronutrient for both plant and animal. Magnesium is often associated with calcium in all kind of water, but its concentration remains generally lower than the calcium [29]. The highest amount of chloride is seen in summer and lowest during post monsoon season. The higher concentration of chloride is considered to be an indicator of higher pollution due to higher organic waste of animal and plant origin. Both phosphate and nitrate are the key nutrients that



cause extensive algal growth, i.e. eutrophication in water bodies. Higher concentration of phosphate is an indicator of pollution, which induce possibility of eutrophication [30]. Lower concentration of nitrite in summer and monsoon may due to the utilization by eutrophication [31]. The N:P ratio is an indicator of the limiting factors of growth of algae in eutrophic water bodies [32]; when the P concentration in water is low vis a vis N, it can be a limiting factor inducing eutrophication symptoms, such as algal blooms [33]. Algal species, which have the potential to compete and survive in these nutrient limiting conditions, dominate the scenario. Such nutrient conditions can also stimulate the production of allelochemicals in certain microalgal species and exert an adverse effect on other algae, thereby inhibiting their growth [9]. 4.3. Phytoplankton composition, abundance and biomass Microalgae are an important part of such eutrophic water systems and their composition/ diversity is greatly influenced by the composition of nutrients and contaminants in the system. Bhat and Pandit [34] found a close relationship between physico-chemical characters of water and growth and abundance of phytoplanktons. They observed high growth of phytoplankton during summer and a very low growth during monsoon. This variation in phytoplankton number may be due to high temperature. The quantity of an aquatic ecosystem depends upon the physical, chemical characteristics as well as on its biological diversity [35]. Temperature is a key factor for the occurrence of phytoplankton as observed in the present study and also reported by Hassan et al. [36]. The rate of decomposition is high during summer due to increase in temperature due to which the water becomes nutrient rich and the nutrient concentration increases and abundant food present in form of photosynthesis [37]. The high phytoplankton population density during the summer season could be related to stable hydrological factors and low water level; while low density during the monsoon season attributed to heavy flood and fresh water inflow. They were resumed again in monsoon due to dilution and high water level [38]. The limiting nutrient concentrations vary with season, location

and phytoplankton community structure [39], and phosphate is one of the important organic nutrients that can limit the phytoplankton population in tropical waters [40]. The composition of phytoplankton during each season was dominated by different species, which most likely adapts to changes in the physical and chemical environment. During summer, phytoplankton assemblages are mainly composed by Cyanophycean species viz., Microcystis aeruginosa, Microcystis flosaquae, Aphanocapsa pulchra, Merismopedia punctata, Aphanotheceae microscopic, Lyngbya shackletoli, Oscillatoria curviceps, Oscillatoria subbrevis, Spirulina major, Spirulina princeps, Anabaena spiroides, Nostoc pruniforme, Oscilltoria tenuis and Aphanocapsa grevillei. Cyanophyceae is one of the major groups of phytoplankton which is mostly confined to the freshwater zones. The relative abundance of Cyanophycean members may be a function of nutrient (N:P) ratios in water bodies [41, 42]. The occurrence of this group could be attributed to the high temperature, slightly alkaline conditions and nutrient rich freshwater discharge, turbidity due to suspended sediment which favors the growth [43]. In general, Cyanobacteria have higher temperature optima for growth than other algal groups, and hence elevated temperatures are found to favour abundance of Cyanobacteria [44]. Dissolve oxygen, pH, alkalinity play a significant role in distribution of Chlorophycean members in freshwater zones [45]. The Chlorophyceans were reported to be dominant during winter season, as also reported by Tiwari and Chauhan [46], that might be due to high DO, high nutrient status and slow water current during this period. In more recent years phosphorus and nitrogen have been identified as components that typically limit the growth of Bacillariophyceae or diatoms under natural conditions. Bacillariophyceae were represented by 15 species. Diatoms are considered to be the best indicators of quality and tropic status of the water body [47]. Temperature and pH will play key role in the distributions of diatoms and abundance of diatoms will be more in colder months. The Euglenophyceae is basically a group of unicellular flagellates. Euglenoids grow luxuriantly and often develop in to water blooms in water, which are organically rich. Hassan et al. [37],



reported minimum density of phytoplankton during monsoon and maximum during summer. When there are favorable conditions such as light and nutrients, phytoplankton tends to increase in abundance and biomass as can reflect by chlorophyll ‘a’ concentrations. Jouenne et al. [48] stated that phytoplankton composition varies with season and this can be ascribed to variation in nutrient access, light and temperature. Rey et al. [49] suggested that besides their importance as the primary producers in food webs and ensuring ecological balances, species of phytoplankton can be useful indicators of water quality. As demonstrated in other geographical areas and variety of habitat types, freshwater influence is known to have profound effect on phytoplankton biomass, productivity and community composition [50]. In addition, pigment signatures allowed us to determine the relative contribution of major phytoplankton groups to total biomass being monitored as chlorophyll ‘a’ concentration, based on the abundance of specific accessory pigments [51]. When there are favourable conditions such as light and nutrients, phytoplankton tends to increase in abundance and biomass as can reflect by chlorophyll ‘a’ concentrations.

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