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553

NSave Nature to Survive

ISSN: 0973 - 7049

: Special issue, Vol. 2;

Paper presented in International Conference onEnvironment, Energy and Development (from

Stockholm to Copenhagen and beyond)December 10 - 12, 2010, Sambalpur University

PHYTOPLANKTON ABUNDANCE AND DIVERSITY IN THE

COASTAL WATERS OF KALPAKKAM, EAST COAST OF INDIA

IN RELATION TO THE ENVIRONMENTAL VARIABLES

M. Smita Achary et al.

East coast of India

Bay of Bengal

Phytoplankton

Water quality

Marine environment

553-568; 2010

554

NSave Nature to Survive

M. SMITA ACHARY*, GOURI SAHU1, A. K. MOHANTY1, M. K. SAMATARA, S. N.

PANIGRAHY1, M. SELVANAYAGAM, K. K. SATPATHY1, M. V. R. PRASAD1 AND

R. C. PANIGRAHY2

Loyola College, Chennai - 600 034, T.N., INDIA1Environmetal and Industrial Safety Section, Safety Group,

Indira Gandhi Center for Atomic Research, Kalpakkam - 603 102, T.N., INDIA2 Department of Marine Sciences, Berhampur University- 760 007

E mail:[email protected]

Phytoplanktons are the base of aquatic food web constitutes the most pivotal biological component

in an aquatic ecosystem. In view of the importance and scarcity of reports from the locality, an

investigation was carried out on a monthly interval during March 2008 and February 2009 in the

coastal waters of Kalpakkam, east coast of India, to assess the seasonal variability in phytoplankton

community structure and related physicochemical parameters. A total of 186 species were observed

during the study, which is about 3 times more when compared to the earlier studies from this

locality. Lowest cell density was observed in January with 0.18×105 cells l-1 at 0.5km and

0.13×105 cells l-1 at 4 km. The reduction in abundance of phytoplankton was observed during

monsoon period, which could be mainly attributed to the low saline water. Highest phytoplankton

population densities for 0.5km and 4 km samples were observed as 4.09 ×105 (August) and

2.31 ×105 cells l-1 (July) respectively. Interestingly, throughout the study, phytoplankton abundance

was observed to be higher at the 0.5km stations when compared to the 4km. Temporally, the pre-

monsoon period (July-September) showed moderately high phytoplankton abundance. A gradual

decrease in cell density was observed during monsoon months (Nov-January) followed by February/

March (post-monsoon), which could be ascribed to the low light penetration and low salinity

conditions with the onset of monsoon. Phytoplankton community was predominated mainly by

diatoms followed by dinoflagellates. Among diatoms, dominant forms were Asterionellopsis

glacialis, Thalassionema nizsvhioids, Biddulphia longicuris, Chaetoceros lorenzianus and among

dinoflagellates, Trichodesmium erythraeum, Protoperidinium grande and Peridinium sp. were

found abundant. Relative contribution of different groups indicated pennate diatom (30.2%),

centric diatom (56.3%), dinoflagellate (8.02%), Silicoflagellate (0.28%) and cyanobacteria (5.69%).

It was observed that salinity strongly correlated with phytoplankton (p≤ 0.01), whereas, temperature

showed moderate positive correlation (p≤ 0.05) with chl-a. Furthermore, transparency was found

to be significantly correlated (p≤ 0.1) to transparency and chl-a. Among nutrients, phosphate

established strong positive correlation (p≤ 0.01) with chlorophyll.

ABSTRACT

*Corresponding author

555

INTRODUCTION

The Phytoplankton community is very vital in the food web dynamics of the sea. About 90% of the total

production in marine ecosystem is contributed by the phytoplankters. Phytoplanktons are primary producers

form the base of food webs that support commercial fisheries, in the marine environment (Sridhar et al.,

2006, Saravanakumar et al., 2008, Mathivanan et al., 2007). These precious denizens constitute several

groups, among which diatoms are one of the most prominent phytoplankton species with respect to abundance

and photosynthetic capabilities within coastal waters and provide about 25%of global net productivity (Lalli

et al., 1997). Diatoms and other dominating phytoplankton constitute a fundamental link in aquatic food

webs and contribute significantly to the biogeochemical fluxes and cycles within the ecosystem (Lalli et al.,

1997; Miller, 2004). As a result, phytoplankton, especially diatoms, remains a subject of increased interest

with respect to global warming and the effects of carbon dioxide (CO2) emissions in the atmosphere (Miller,

2004). Phytoplankters undergo changes in their distribution due to change in the physical, chemical and

biological factors. The species composition and population density of phytoplankton are sensitive to

environmental changes and continual documentation of phytoplankton population dynamics can provide an

invaluable record of water quality. Moreover, the photosynthetic fixation of inorganic carbon by phytoplankton

offers a source of organic carbon and energy for higher trophic levels. The understanding of phytoplankton

dynamics (i.e. changes in population abundance, composition and distribution, and rates of physiological

processes) is, therefore, central to the understanding of how coastal water ecosystems work and how they

respond to stresses imposed by man and nature. Two important environmental factors are recognized as

controlling community structure of phytoplankton. The first is related to physical processes, such as mixing

of water masses, light, temperature, turbulence, and salinity, and the second is associated with chemical

aspects i.e. nutrients (Reynolds, 1984). In view of this, the present study was carried out in coastal areas of

Kalpakkam southeast coast of India, offering an opportunity to analyze the effect of local hydrology and

human activities on water quality and phytoplankton communities. An array of information with respect to

phytoplankton dynamics is available from the Indian coastal waters such as Trivandrum coast (Menon,

1945), west coast of India (Subramanyan and Sarma, 1961), grade zone of Vellar estuary (Chandran, 1985),

Madras coast (Subramanyan, 1946, 1968; Desikachary, 1987), Cuddalore Uppanar backwater (Murrugan

and Ayyakkannu, 1993) and Gopalpur coast (Gouda and Panigrahy, 1996). However, a paucity of extensive

studies along the south east coast of India in general and from the Kalpakkam coastal waters in particular

has motivated to carry out the present investigation. The prime objectives of the present study, (i) to create

a baseline data for the future reference and assess the qualitative and quantitative abundance and changes

with time, (ii) to observe the impact of environmental dynamics on phytoplankton community.

MATERIALS AND METHODS

Study area

Kalpakkam is situated at 12º33’ N Lat and 80º11’ E Long along the Indian east coast. At present a nuclear

power plant (Madras Atomic Power Station, MAPS) and a desalination plant are located near the coast. The

important feature of this coast is the presence of two back waters namely, Edaiyur and Sadras back water

systems. During the period of northeast monsoon and seldom during southwest monsoon, these two back

waters get opened to the sea (2/3 months only) discharging considerable amount of fresh water into the

coastal environment. According to the climatology of this area the whole year has been divided into 3

seasons. Viz. (i) Post-monsoon/ summer (Feb-May) (ii) Pre-monsoon or SW monsoon (June-September) and

NE monsoon (October-January). Due to the geographic location of this area, the monsoon reversal of wind

and the subsequent change in the current pattern is prominent here.

Methods

Samples were collected on monthly basis during March 2008 and February 2009 from two transects parallel

to the coastline (T1-0.5km and T2 4km offshore). Each transect consist of 6 stations depending on the point

PHYTOPLANKTON ABUNDANCE AND DIVERSITY IN THE COASTAL WATERS

556

sources (Fig. 1) of anthropogenic pollutants. Samples were collected for phytoplankton chlorophyll-a and

physico-chemical parameters such as temperature, salinity, pH, Dissolved oxygen (DO), turbidity and

nutrients (nitrite, nitrate, ammonia, total nitrogen (TN), silicate, phosphate and total phosphorous (TP).

The station locations are related to the point sources of anthropogenic input and are elaborated as Control(A1),

Sadras back water(B1), Fishing village(C1), Jetty(D1), Edaiyur(E1) and Mahabalipuram (F1) (Fig. 1) situated

2km apart. The water temperature was measured onboard the boat by a mercury thermometer having ±1ºC

accuracy. pH of the water samples were carried out by a pH meter ( Cyberscan PCD 5500) having a

resolution of 0.01. DO content was estimated adopting Winkler’s method (Parson et al., 1984). Turbidity

content was measured by turbidity meter (Cyberscan IR TB 100) having 0.01 NTU resolution. Salinity was

measured as per Knudsen’s method (Parsons et al., 1984). Nutrient estimation was done following the

spectrophotometer methods of (Parsons et al., 1984). For qualitative as well as quantitative studies of

phytoplankton, 1L of surface seawater sample was collected in acid cleaned polyethylene bottles and fixed

with 5% formaldehyde solution. From the above concentrated sample, 1ml was taken on a Sedge-wick

Rafter cell for analysis under a binocular research microscope (NIKON Eclipse 50i) for counting.

Identification of phytoplankton was carried out referring standard phytoplankton identification manuals

(Subramanyan, 1946; Desikachary, 1987 and Tomas, 1996). Chl-a was estimated using a double beam UV–

Visible Spectrophotometer (Chemito Spectrascan UV 2600) following the method of Parsons et al. (1984).

Three diversity indices such as species diversity (D), species richness (R) and evenness (J) were computed

to evaluate the variation in plankton community structure and diversity, using the formula:S

e1

D = P i lo g P ii =

⎛ ⎞−⎜ ⎟⎝ ⎠

∑ (Shannon-Weaver, 1963), where, Pi = proportion of individuals in the ith species; species

richness e

S - 1R =

l o g N

⎛ ⎞⎜ ⎟⎝ ⎠

(Gleason, 1922; Endorsed by Margaleaf, 1960), where, S = Number of species in the

population and N= Number of individuals in the population and evenness e

DJ=

log S

⎛ ⎞⎜ ⎟⎝ ⎠

(Pielou, 1966), where,

D=Species diversity. Cluster analysis was carried out to find out similarity as well as dissimilarity among

different time periods with respect to different variables. Principal Component Analysis (PCA) was carried

out to compress the data by reducing the number of dimensions to determine the variability of phytoplankton

with respect to the physicochemical properties. Simple correlation analysis was carried out to correlate all

the parameters with one another. All the above statistical analyses were carried out using XL- Stat software.

RESULTS

Hydrodynamics

Hydrobiological variables showed pronounced variation during the present investigation. Surface sea water

temperature ranged from 26.90ºC (July) to 30.88ºC (March) indicating the annual range of ~3.98ºC (Table

1). Transect wise no significant difference in temperature was observed during the study period. pH was the

minimum 7.49 during October and maximum during 8.24 during August. Like temperature pH also did not

show any marked variation throughout the study period and difference between the two transects. pH showed

negative correlation (p≤0.1) with temperature (Table 2). Salinity values fluctuated between 24.45 psu and

36.72 psu. The lowest and highest values were observed during November and May respectively. During

monsoon period relatively low salinity was observed compared to other period. Between two transects, no

significant variation was observed as was found in case of temperature and pH. Salinity was positively

correlated with temperature which was seen in the correlation (p≤0.1) matrix. Dissolved oxygen (DO),

values were the lowest 6.21 mg L-1 during May and highest during 9.35 mg L-1 during August. Relatively high

DO values were recorded during pre-monsoon and monsoon period. Predictably DO established a negative

correlation (p≤0.1) with salinity. Turbidity values varied from 0.34 and 5.79 Nephelometric Turbidity Unit

(NTU) during the months June and May respectively. It was observed that during summer and monsoon

turbidity values were at higher side. Interestingly stations located in the 1st transect (500m) showed relatively

high turbidity values compared to the 2nd transect (4km). Turbidity yielded negative (p≤0.05) correlation

with DO during this study. Secchi disc depth was the lowest 0.78cm during May and highest 11.19cm during

M. SMITA ACHARY et al.,

557

Date Location Temp. pH Salinity DO Turb. Secchi Chl-a

Min- Max(Mean)

March T 1 29.90-31.00 7.68-8.16 33.85-36.38 6.65-7.90 0.54-2.16 4.22-8.25 0.815-4.3652

(18.03.08) (30.42) (7.99) (35.74) (7.28) (1.09) (6.41) (2.011)

T 2 30.50-31.40 7.76-8.21 35.33-36.33 7.30-8.45 0.22-2.90 5.72-15.20 1.637-4.7604

(30.88) (7.98) (35.72) (7.83) (1.11) (10.13) (3.067)

April T 1 30.50-31.00 8.13-8.19 36.06-36.30 6.50-6.95 0.52-4.05 1.75-5.02 1.163-3.27

(29.04.08) (30.67) (8.16) (36.2) (6.76) (1.72) (2.95) (2.27)

T 2 30.50-31.00 8.10-8.17 36.21-36.28 6.95-7.25 0.29-1.30 9.75-9.95 1.163-1.2244

(30.83) (8.12) (36.24) (7.12) (0.75) (9.85) (1.194)

May T 1 29.40-30.00 7.87-8.04 36.58-36.83 6.00-6.50 3.41-6.81 0.40-1.25 1.163-5.4256

(14.05.08) (29.8) (7.94) (36.73) (6.39) (5.79) (0.78) (2.337)

T 2 29.00-29.80 7.91-8.14 36.61-36.84 6.00-6.80 0.25-1.15 4.75-8.70 0.288-5.2596

(29.2) (8) (36.72) (6.21) (0.46) (6.35) (1.753)

June T 1 26.80-27.50 7.67-8.05 35.48-36.08 6.45-8.35 1.27-3.81 1.50-4.30 2.52-3.4648

(17.06.08) (27.17) (7.95) (35.79) (7.5) (2.23) (3.18) (3.227)

T 2 27.20-28.10 7.80-8.28 35.68-35.98 6.45-8.05 0.18-0.57 1.50-4.00 2.108-3.9388

(27.67) (8.09) (35.84) (7.28) (0.34) (2.33) (3.196)

July T 1 26.70-27.40 7.72-8.02 35.20-35.52 5.75-7.80 1.19-6.18 1.25-1.75 0.28-1.2244

(16.07.08) (27.08) (7.88) (35.4) (6.89) (3.7) (1.42) (0.871)

T 2 26.50-27.20 7.90-8.04 35.30-35.56 5.60-7.35 0.21-3.72 3.25-4.25 0.815-1.234

(26.9) (7.98) (35.37) (6.52) (1.2) (3.75) (1.148)

Aug T 1 28.30-28.90 7.95-8.20 35.62-36.02 8.10-9.05 1.97-5.19 1.75-2.75 1.357-3.6008

(22.08.08) (28.5) (8.05) (35.85) (8.54) (3.41) (2.32) (2.141)

T 2 28.30-28.60 8.17-8.52 35.43-35.89 8.80-10.35 0.20-0.47 7.70-9.75 1.292-1.708

(28.43) (8.24) (35.7) (9.35) (0.37) (8.66) (1.453)

September T 1 29.00-29.00 7.98-8.08 36.22-36.43 7.15-7.90 4.28-7.04 1.10-1.30 1.234-2.2404

(22.09.08) (29) (8.04) (36.33) (7.51) (5.43) (1.16) (1.974)

T 2 27.50-28.00 8.09-8.17 35.87-36.28 6.70-8.65 0.41-1.84 4.15-5.75 1.234-1.6368

(27.77) (8.13) (36.13) (7.57) (1.11) 5.23 (1.339)

October T 1 30.00-32.50 5.65-7.94 27.04-28.21 7.25-8.65 0.62-2.03 2.30-3.90 1.999-4.89

(24.10.08) (30.57) (7.49) (27.56) (7.7) (1.01) (3.04) (2.649)

T 2 30.30-30.50 6.54-8.14 26.98-28.34 7.40-9.20 0.35-1.97 5.90-7.75 0.761-0.8184

(30.33) (7.78) (27.5) (8.12) (0.97) (6.73) (0.804)

November T 1 27.10-28.80 7.86-8.21 18.98-26.00 6.90-8.15 0.55-13.78 0.80-4.30 1.292-2.1756

(05.12.08) (27.98) (8.03) (24.45) (7.37) (5.1) (1.98) (1.881)

T 2 27.70-28.20 7.87-8.17 25.48-26.07 7.40-8.35 0.82-1.92 4.30-6.25 0.474-0.8184

(27.9) (8) (25.88) (7.98) (1.38) (5.17) (0.646)

December T 1 26.60-27.30 7.83-8.16 28.73-28.99 7.25-7.75 0.54-2.45 2.25-6.50 0.065-2.1756

(30.12.08) (26.97) (8.08) 28.86 (7.5) (1.39) (3.08) (0.947)

T 2 27.20-27.50 8.0-8.25 29.12-29.32 7.30-7.55 0.52-1.33 2.75-8.50 0.126-0.948

(27.32) (8.13) (29.16) (7.41) (0.89) (6.91) (0.515)

January T 1 26.90-28.60 7.60-8.20 30.29-30.49 6.60-7.15 0.43-4.14 1.40-2.60 2.172-2.17

(28.01.09) (27.67) (8.02) (30.4) (6.96) (1.91) (2.12) (2.172)

T 2 26.90-28.20 7.60-8.20 30.55-30.62 6.95-7.75 0.31-1.79 7.50-11.10 0.40-1.6984

(27.52) (7.93) (30.56) (7.21) (0.89) (9.51) (1.051)

February T 1 27.70-31.40 7.60-8.10 32.76-33.02 6.20-7.00 1.32-8.12 1.75-3.10 1.702-2.234

(21.02.09) (28.75) (7.92) (32.97) (6.58) (3.4) (2.28) (2.015)

T 2 27.60-28.50 8.00-8.20 32.76-32.96 6.55-7.10 0.93-2.70 10.20-12.00 1.292-1.76

(28.03) (8.15) (32.9) (6.78) (1.44) (11.19) (1.612)

Table 1: Monthly min, max and mean values of different physico-chemical parameters

Feb/March. Relatively low transparency was observed during pre-monsoon and monsoon period. Between

two transects, the 2nd transect showed values at higher level compared to the 1st transect. A negative

correlation was established between secchi disc depth (p≤0.05) and turbidity.

Nutrient

Dissolved inorganic nutrients also showed marked variation during throughout the study period (Table 3).

Nitrate was the minimum 0.20 μmolL-1 and maximum 5.93 μmolL-1 during March and January respectively.

Comparatively low nitrate values were observed during post-monsoon/summer period. In the month of June


558

difference between the two transects with respect to nitrate concentration was the highest compared to

other months. No correlation was established between nitrate and other parameters except nitrite. As in

case of nitrate, nitrite also indicated lower values during post-monsoon/summer period. NH3 was the highest

during December in both the transects. April and June showed lowest values during the study period. Post-

monsoon/Summer months indicated relatively low concentration of NH3 in comparison with monsoon and

pre-monsoon period. In the month of July, the variation between two transects was the highest. NH3 yielded

a strong negative relation with salinity. It showed negative correlation (p≤0.01) with phytoplankton and

Variables Temp. pH Salinity DO Turb. Secchi NO3 NO2 NH3 TN PO4 TP Si phyto Chl-a

Temp. 1

pH -0.152c 1

Salinity 0.158 c 0.190 b 1

DO -0.157 c 1

Turb. -0.172 b 1

Secchi 0.181 b 0.152 c -0.196 b 1

NO3 -0.253 a 1

NO2 0.715 a 1

NH3 -0.317 a -0.576 a 1

TN -0.160 c 1

PO4 0.183 b 0.579 a 1

TP 0.379 a 0.753 a 1

Si -0.230 a -0.243 a 0.292 a 0.199 b 1

Phyto 0.302 a -0.273 a 1

Chl-a 0.201 b -0.191 b 0.166 b 0.142 c 0.199 b -0.246 a -0.172 b 0.239 a 0.156 c 1

(p=Significance level): a-p≤0.01, b-p≤0.05, c-p≤0.1

Table 2: Correlation matrix of the physico-chemical parameter

Chlorophyll-a also. TN concentration was obtained

relatively at lower side during Post monsoon/Summer.

Transect wise difference was found to be negligible

during maximum months except July and September.

A good negative correlation was found between TN

and Chlorophyll-a. PO4

showed a noticeable increase

from March-November followed by a sharp decline

from December and continued till February. TP

concentration was relatively low during Post-monsoon

and monsoon period. The highest value for 500m

transect was found during May and for 4km during

June. The maximum variation between two transects

was observed during June. As expected, TP should

positive correlation with PO4 . Silicate values showed

relatively high values in 500m samples compares to

4km samples. During monsoon period, silicate

concentration was found to be high in comparison

with other period of the study period. Silicate showed

strong negative correlation (p≤0.01) withty.

Phytoplankton (Qualitative and quantitative aspects)

Qualitative aspects (Species composition)

The plankton flora comprised of 186 sp; 153 Diatoms,

26 dinoflagellates, 2 Cyanobacteria, and 2

Silicoflagellates. (Table 5) Diatoms formed the most

dominant (86.5%) group followed by dinoflagellate

(8.02 %), cyanobacter ia (5.69 %) andFigure 1: Location of different sampling stations in study

area

12º37’35.04”N

80º7’38.02”E

12º37’35.04”N

80º7’38.02”E

12º29’12.69”N

80º7’38.02”E

12º29’12.69”N

80º7’38.02”E


559

silicoflagellates (0.28 %).

The diatom flora comprised of 97 centrales, 59 pennales. Among the centrales, 13 no families such as

Hemiaulaceae, Asterolampraceae, Coscinodiscaceae, Hemidiscaceae, Leptocylindraceae, Melosiraceae,

Thalassiosiraceae, Rhizosoleniaceae, Chaetocerotaceae, Eupodiscaceae, Lithodesmiaceae, Licmophoraceae

and triceraceae were found floristically richer than the others, while in case of pennales, 8 Families such

as Fragilariaceae, Striatellaceae, Rhaphoneidaceae, Thalassionemataceae, Achnanthaceae, Naviculaceae,

Cymbellaceae and Licmophoraceae were dominated the diatom community. Monthly variation in no of

phytoplankton sp is given in (Fig. 3). No of phytoplankton species ranged from 7-71 in the 1st transect and 11-

62 in the 2nd transect. The lowest no of sp in both the transects was observed during February, while the

highest no was found during January in case of 1st transect and during December in 2nd transect. Relatively

high no of species was observed during monsoon period compared to post-monsoon and pre-monsoon. An

abrupt decline was observed during October in both of the transects. Next to October in February another

decline in no of species was notices in both the transects. Stationwise variation in no of species showed

remarkable difference between 1st and 2nd transect. The 1st transect was found to be richer in phytoplankton

species from station-1 to station-4. However, a sudden alteration was observed in station-5 and station-6,

where the 2nd transect exceeded the first transect.

Among diatoms were Asterionellopsis glacialis, Thalassionema nizsvhioids, Biddulphia longicuris, Chaetoceros

lorenzianus were found to be dominant. Similarly, dinoflagellate community was dominated by Trichodesmium

erythraeum, Protoperidinium grande and Peridinium sp.

Quantitative aspect (Population density and distribution)

Monthwise and stationwise variations are given in (Fig. 2 and 4). Well marked monthly variation was

observed in population density of phytoplankton. The lowest (0.18-1st transect; 0.13 2nd transect) and densities

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb

A-Near shore B-4 Km inside

Month

Cal

l den

sity

(x 1

05 c

ells

L-1)

Figure 2: Month wise variations in phytoplankton density

were observed in the month of January for both the transects, whereas the highest density in 500m (1st

transect) transect was observed during August and in 4km transect during July. In contrast to the no of

species, phytoplankton density was found to be relatively at lower side compared to other timings of the

study period. Relative contribution of different phytoplankton groups are as follows: Centric (56.3 %),

pinnate (30.2 %), cyanobacteris (5.69 %) and silicoflagellate (0.28 %). Between the two groups of diatom,

centrics were predominated pennates during the entire study period. The succession of phytoplankton species

was mainly controlled by salinity regime; hence categorization of these species has been made according to

their salinity tolerance.

Diversity indices

Diversity index parameters (Species Diversity, species richness and evenness) are given in (Fig. 5). No

marked variation was seen in case of species diversity in the present study. Same is the case in evenness.

However, in species richness well pronounced variability was noticed. The lowest (0.86) species richness

value negative was observed during February and the highest (12.15) during January. This trend of species

richness was almost analogous to the qualitative trend of phytoplankton.

0

10

20

30

40

50

60

70

80

90

Mar08 Apr 08 May08 Jun 08 Jul 08 Aug 08 Sep 08 Oct 08 Nov 08 Dec 08 Jan 09 Feb09

Near Shore 4 km inside

Month

No. of Spec

les

Figure 3: Monthly variation in no of phytoplankton species


560

Dat

eL

oca

tion

NO

3N

O2

NH

3T

NPO

4T

PSi

Min

- M

ax(M

ean)

Mar

ch(1

8.0

3.0

8)

T 1

0.2

1-0

.25(0

.22)

0.0

9-0

.26(0

.18)

0.7

7-3

.31(1

.6)

2.2

8-1

0.5

8(7

.4)

0.1

8-0

.59(0

.39)

0.2

7-0

.73(0

.44)

7.4

3-2

6.5

5(1

1.2

)

T 2

0.1

7-0

.23(0

.2)

0.1

5-0

.24(0

.19)

0.1

7-1

.82(0

.99)

7.2

6-8

.51(7

.95)

0.3

-0.5

5(0

.45)

0.1

4-0

.41(0

.33)

5.7

8-1

4.4

8(9

.58)

Apri

l(29.0

4.0

8)

T 1

0.1

7-1

.04(0

.34)

0.0

0-0

.07(0

.02)

0.0

0-0

.33(0

.17)

0.0

0-9

.34(8

.91)

0.0

0-0

.41(0

.19)

0.0

9-0

.50(0

.3)

0.0

0-1

0.6

5(6

.81)

T 2

0.1

7-0

.29(0

.22)

0.0

2-0

.06(0

.03)

0.0

6-0

.50(0

.26)

5.4

0-9

.13(7

.68)

0.0

5-0

.09(0

.06)

0.0

0-0

.00(0

.25)

4.4

3-1

3.5

0(7

.73)

May

(14.0

5.0

8)

T 1

0.0

6-1

.56(0

.57)

0.0

7-1

.24(0

.33)

0.6

6-6

.83(2

.76)

0.0

0-9

.75(9

.52)

0.0

5-1

8.3

6(0

.56)

0.0

0-1

4.4

7(2

.53)

4.8

8-1

1.4

8(8

.79)

T 2

0.0

2-1

.56(0

.82)

0.0

0-0

.39(0

.22)

0.0

0-5

.90(1

.69)

0.0

0-1

5.1

5(8

.5)

0.0

9-9

.09(0

.47)

0.0

0-1

0.1

8(2

.15)

3.7

5-1

8.6

0(9

)

June(

17.0

6.0

8)

T 1

0.0

4-0

.46(0

.22)

0.1

7-2

.84(0

.89)

0.1

1-0

.55(0

.3)

1.4

5-1

6.1

9(8

.5)

0.1

8-1

.10(0

.55)

0.2

3-0

.91(0

.49)

3.9

8-7

7.4

0(1

4.7

)

T 2

0.6

2-5

.27(2

.6)

0.0

0-0

.61(0

.29)

0.0

0-0

.61(0

.3)

1.6

6-1

1.0

0(6

.23)

0.2

3-0

.96(0

.59)

0.2

3-1

4.1

1(2

.68)

7.1

3-2

4.0

0(1

3.6

9)

July

(1

6.0

7.0

8)

T 1

0.8

7-3

4.9

4(2

.72)

0.0

7-2

8.9

6(3

.39

0.5

0-2

8.9

4(5

.66)

3.3

2-2

7.1

8(1

6.1

9)

0.4

1-2

.74(0

.22)

.82-2

.60(1

.76)

7.3

5-3

1.3

5(1

6.1

3)

T 2

0.0

4-1

0.1

1(3

.63)

0.0

7-1

1.1

1(1

.97)

0.3

3-1

.76(1

.07)

10.3

8-9

3.7

9(2

5.4

9)

0.5

9-1

.74(0

.27)

0.7

3-3

.70(1

.57)

5.2

5-1

8.1

5(1

2.0

4)

Aug(2

2.0

8.0

8)

T 1

0.0

2-6

.66(1

.36)

0.0

0-0

.76(0

.2)

0.2

8-1

.71(0

.84)

1.6

6-4

3.5

8(1

4.1

1)

0.0

5-0

.64(0

.43)

0.1

4-2

.05(1

)1.6

5-2

3.6

3(8

.11)

T 2

0.3

3-1

.47(0

.8)

0.0

0-1

.02(0

.22)

0.2

2-2

.76(1

.55)

4.3

6-1

2.4

5(1

2)

0.0

9-1

.37(0

.46)

0.3

7-2

.88(1

.44)

0.3

0-2

3.7

8(7

.16)

Sep

tem

ber

(22.0

9.0

8)

T 1

0.6

8-5

.85(2

.3)

0.1

5-3

.56(1

.16)

1.1

6-4

.30(2

.48)

7.8

9-2

2.4

1(1

0.5

8)

0.5

9-1

.69(0

.96)

0.5

9-1

.51(1

.06)

4.2

0-1

1.1

0(7

.58)

T 2

0.3

9-2

.99(1

.27)

0.3

7-0

.78(0

.61)

0.5

0-2

.65(1

.5)

5.1

9-5

3.1

2(2

5.9

4)

0.0

9-0

.82(0

.63)

0.4

6-1

.60(1

.01)

4.4

3-1

3.5

8(9

.68)

Oct

ober

(24.1

0.0

8)

T 1

0.2

4-4

.52(2

.2)

0.3

7-2

.01(0

.7)

0.6

2-7

.02(3

.25)

0.4

1-6

.30(1

2.5

)0.5

0-8

.10(0

.82)

0.2

0-7

.40(0

.95)

0.2

0-7

.30(1

5)

T 2

0.3

1-7

.02(2

.3)

0.1

30-8

.10(0

.4)

0.0

2-5

.2(2

.3)

0.7

0-3

.80(1

3.4

)0.1

2-6

.30(0

.57)

0.5

0-6

.30(0

.98)

0.4

1-6

.30(1

0)

Novem

ber

(05.1

2.0

8)

T 1

0.3

5-6

.23(2

.65)

0.2

6-0

.48(0

.41)

7.6

6-1

4.7

7(1

1.4

2)

4.1

5-2

5.1

1(1

8.8

6)

0.3

2-1

.19(1

.17)

0.2

7-1

.05(0

.75)

9.7

5-7

7.7

0(2

5.3

8)

T 2

1.3

9-6

.66(3

.64)

0.1

3-0

.54(0

.4)

8.2

1-1

3.3

4(1

0.4

4)

10.5

8-1

5.5

6(1

8.2

4)

0.3

2-0

.59(1

.72)

0.5

9-1

.05(0

.75)

6.6

8-1

3.2

8(1

0.6

9)

Dec

ember

(30.1

2.0

8)

T 1

0.1

0-1

.10(0

.46)

0.1

1-0

.17(0

.15)

5.9

0-2

3.4

8(1

7.8

9)

4.9

8-1

0.3

8(2

2.7

1)

0.0

9-0

.32(1

.61)

0.3

2-1

.19(0

.62)

13.8

0-2

6.6

3(1

8.5

3)

T 2

0.1

9-1

.18(0

.45)

0.0

7-0

.22(0

.13)

17.3

1-2

5.1

3(2

0.5

1)

3.1

1-7

.68(2

5.8

8)

0.1

8-0

.41(1

.39)

0.0

5-1

.42(0

.68)

10.5

8-2

7.0

0(1

7.3

1)

Januar

y(2

8.0

1.0

9)

T 1

4.1

9-6

.45(5

.57)

0.1

1-3

.36(0

.79)

0.1

1-2

.43(0

.75)

4.5

7-3

1.5

4(1

2.7

3)

0.1

8-0

.46(0

.3)

0.0

5-0

.55(0

.25)

8.7

8-1

0.5

0(1

9.7

)

T 2

5.6

9-6

.33(5

.93)

0.1

1-1

.19(0

.48)

0.6

1-7

.17(3

.55)

4.1

5-1

9.7

1(1

2.5

8)

0.0

9-0

.32(0

.21)

0.1

4-1

.74(0

.5)

4.9

5-1

3.2

0(1

8.4

1)

Feb

ruar

y(2

1.0

2.0

9)

T 1

0.0

0-1

.74(0

.75)

0.1

5-0

.93(0

.49)

2.1

5-1

0.9

1(5

.5)

3.9

4-3

9.0

1(1

7.2

6)

0.0

0-0

.46(0

.22)

0.3

2-0

.59(0

.47)

4.5

8-7

5.3

8(1

7.5

1)

T 2

0.0

0-1

.35(0

.6)

0.1

1-0

.30(0

.19)

0.9

4-1

0.9

1(5

.72)

5.8

1-1

6.6

0(1

1.5

9)

0.0

0-0

.50(0

.19)

0.5

0-2

.74(1

.03)

1.2

8-8

1.5

3(1

7.2

)

Table

3:

Month

ly m

in,

max a

nd m

ean v

alu

es o

f dif

fere

nt

nutr

ients

obse

rved

duri

ng s

tudy p

erio

dPhotosynthetic pigment

Photosynthetic pigments showed a wide

variation and ranged between 0.51 mg

m-3 and 3.22 mgm-3. The seasonal

fluctuation of Chl-a is corresponding

to the phytoplankton density trend.

DISCUSSION

Hydrodynamics

Temperature is an important

environmental variable, which affects

an array of chemical and biological

interactions. The annual range of

temperature during the present study

matches with the reported variations

from Gouda and Panigrahy,

1996.During the present study two

maxima were observed, one during

April/May and another during

September/October. This is well

understood that in the southeast coast

of India two maxima in atmospheric

temperature are observed in a year,

One in April/May and another during

September/October. This observation

was in agreement with the earlier

report of Satpathy and Nair, 1990. The

atmospheric bimodal oscillation is also

reflected in surface water temperature

variations. Salinity is one of the most

important properties of sea water which

determines the growth and survival of

the ambient life. During monsoon

period the decline in salinity could be

ascribed to the dilution of coastal water

by the influence of precipitation

received during NE monsoon and by

local freshwater discharge from two

backwaters into the coastal water.

With the peak summer condition during

April/May salinity was found to be

raised due to elevated temperature.

This observation was further supported

by the positive correlation established

between salinity and temperature

(Satpathy, 1996). Relative high DO

values during pre monsoon and monsoon

period attributed to the heavy


561

Month

Val

ues

Figure 3: Monthly variation in no of phytoplankton species

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

Mar Apr May Jun Jul Aug Sepr Oct Nov Dec Jan Feb

Species diversity

Species richness

Evenness

September

August

July

March

April

May

June

January

February

November

Sim ilarity

October

December

0.99 0.97 0.95 0.93 0.91 0.89 0.87

Figure 6: Cluster analysis of phytoplankton density and hydrographical parameters

photosynthetic release by autotrophs (phytoplankton)

during pre-monsoon and input of oxygen rich fresh

water to the coastal domain during monsoon period.

As expected, salinity showed a negative influence on

DO (p≤0.1). Turbidity is the key factor which decides

the transparency of the sea water and ultimately

declined the productivity (Quasim et al., 1968).

Comparatively high turbidity during summer and

monsoon period may be due to high phytoplankton

density during which might have created turbid

environment and heavy silt laden freshwater influx


F1 F2 F3 F4 F5 F6 F7

Eigenvalue 3.06 2.24 1.89 1.44 1.33 1.02 0.96

Variability (%) 19.12 14.00 11.83 8.99 8.34 6.36 6.03

Cumulative % 19.12 33.12 44.96 53.94 62.28 68.64 74.67

Factor loadings:

Temp. 0.39 -0.19 -0.34 -0.49 -0.16 -0.03 -0.28

pH 0.09 -0.17 -0.05 0.72 -0.01 -0.34 0.24

Salinity 0.87 -0.24 0.19 0.23 0.11 -0.02 -0.02

DO -0.18 -0.22 0.02 -0.28 -0.45 0.07 0.61

Turb. 0.05 0.37 -0.09 -0.12 0.66 0.08 0.02

Secchi 0.41 0.58 -0.28 -0.02 -0.16 -0.19 -0.10

NO3 -0.15 0.22 0.85 -0.20 0.06 -0.18 -0.02

NO2 -0.02 0.19 0.84 -0.21 -0.02 -0.21 0.04

NH3 -0.67 0.31 -0.23 0.25 -0.12 -0.08 0.09

TN -0.08 0.08 0.29 0.24 -0.12 0.82 -0.18

PO4 0.39 0.82 -0.01 0.06 -0.22 0.07 0.09

TP 0.35 0.71 0.01 0.17 -0.23 0.09 0.17

Si -0.33 0.26 -0.10 0.06 0.66 0.05 0.21

phyto 0.39 -0.28 0.03 -0.08 0.19 0.28 0.52

Chl-a 0.40 0.19 -0.24 -0.49 0.15 -0.02 0.21

Table 4: Principal components Analysis (PCA) of the hydro-biological variables

during monsoon. Predictably, in contrast to the turbidity trend, secchi disc depth showed low values during

pre monsoon and monsoon months. This relationship between secchi depth and turbidity was reflected in the

negative correlation established between them.

562

Diatoms Melosira moniliformis

Division-Chromophyta Stephanopyxis palmeriana (Grev.) Grun.

Class-Bacillariophyceae S. turris

Family – Hemiaulaceae Family – Thalassiosiraceae

Centrics Thalassiosira decipiens

Hemiaulus membranaceus Thalassiosira sp

Hemiaulus sinensis Grev. Thalassiosira subtilis (Ostenf.) Gran

Hemiaulus hauckii Grun. T. eccentrica (Ehrenb.) Cl.

Ceratualina bergonii Cyclotella striata (Kuetz.) Grun.

C. pelagica (Cl.) Hend. C. Kuetzingiana Thw

Order- Biddulphiales C. stylorum

Sub-Order-Coscinodiscineae Lauderia annulata (Grev.) Cl.

Family-Asterolampraceae Skeletonema costatum (Grev.) Cl.

Asteromphalus sp Sub-Order- Rhizosoleniineae

Asteromphalus heptactis Family – Rhizosoleniaceae

A. hiltonianus Proboscia alata (Btw.) Sundstorm

Asterolampra vanheurckii Rhizosolenia hebetata Bail.

Family – Coscinodiscaceae R. hyalina

Coscinodiscus sp R. styliformis Btw.

Coscinodiscus apiculatus R. imbricata Btw.

C. radiatus Ehrenb. R. Stolterfothii H. Perag

C. asteromphalus Ehrenb. R. robusta Norman

C. centralis R. setigera Btw.

C. jonesianus (Grun.) Hust. R. crassispina Schrod.

C. oculus-iridis R. bergonii

C. granii Gough R. castracanei Perag.

C. marginatus Ehrenb. R. cochleaBrun

C. rothii (Ehrenb.) Grun. R. cylindrus

C. subtilis Ehrenb. Dactyliosolen fragillisimus

C. concinnus D. phuketensis

C. gigas Ehrenb. Guinardia flaccida (Castr.) Perag.

Hyalodiscus stelliger Sub-Order- Biddulphiineae

H. radiatus Family – Chaetocerotaceae

Family - Hemidiscaceae Bacteriastrum delicatulum Cl.

Hemidiscus hardmanianus (Grev.) Mann B. furcatum

Hemidiscus sp B. varians

Family – Leptocylindraceae B. comosum Pavill.

Leptocylindrus danicus Cl. B. hyalinum Lauder

L. minimus Gran Family – Triceraceaceae

Corethron hystrix Hensen Triceratium robertsianum

C. enermii T. alternans

Family – Melosiraceae T. broeckii

Melosira nummuloides (Dillwyn) Ag. Triceratium reticulum

Melosira spaerica Pennates

Melosira dubia Order – Bacillariales

Chaetoceros peruvianus Sub-order- Fragilariineae

C. decipiens Hust. Family – Fragilariaceae

C. diversus Cl. Acnanthes sp.

C. curvisetus Cl. Asterionellopsis glacialis Castr.

C. compressus Lauder Fragilaria oceanica Cl.

C. diadema Synedra tabulata

C. atlanticus S. ulna

C. lacineosus S. formosa Hantz.

C. coarctatus Order – Striatellales

C. constrictus Gran Family – Striatellaceae

C. paradoxus Schutt Grammatophora marina

C. lorenzianus Grammatophora sp

C. messanensis Family – Rhaphoneidaceae

C. lauderi Raphoneis amphiceros

C. eibenii Grun. Delphineis surirelloides

Table 5: List of phytoplankton species recorded at Kalpakkam Coast (March 2008- February 2009)


563

An array of inorganic substances plays pivotal roles in the life supporting systems of the aquatic world.

Among nitrogenous nutrients, nitrite, nitrate and ammonia play very important role in the growth and

Chaetoceros sp Family – Thalassionemataceae

Family – Eupodiscaceae Thalassionema nitzschoides

Biddulphia heteroceros Grun. T. bacillare

B. pulchella Sub-order- Bacillariineae

B. aurita (Lyngb.) Breb. and Godey Family – Achnanthaceae

B. rhombus (Ehrenb.) Wm. Smith Acnanthes sp.

B. longicuris Grev. Family- Naviculaceae

B. mobiliensis (Bail.) Grun. Amphiprora hyperborea

B. sinensis Grev. A. gigantea

B. regia A. paludosa

Family – Lithodesmiaceae Amphiprora sp.

Ditylum brightwelli (West) Pleurosigma elongatum

Ditylum sol Grunow in Van Heurck P. formosum W. Smith

Streptotheca indica P. angulatum (Kutzing) W. Smith

Streptotheca thamensis P. aestuarii (Breìbisson) W. Smith

Order – Licmophorales P. directum Grunow

Family – Licmophoraceae P. elongatum W. Smith

Lithodesmium undulatum P. normanii Ralfs in Pritchard

Order – Triceratiales Navicula sp.

Navicula longa N. macilenta Gregory

N.henneydi Perag. and Perag. N. lanceolata Grun.

N.longa (Greg.) Ralfs Pseudonitzschia pungens (Grunow ex Cleve) Hasle

Trachyneis aspera (Ehrenberg) Cleve Pseudonitzschia delicatissima (Cleve) Heiden in Heiden and Kolbe

Gyrosigma balticum (Ehrenberg) Robenhorst Pseudonitzschia australis Frenguelli

Caloneis madrasensis Order – Licmophorales

C. liber (Wm. Smith) Cl. Family – Licmophoraceae

Diploneis sp Licmophora abbreviata

Diploneis crabro (Ehrenberg) Ehrenberg Dinoflagellates

Dilponeis bombus Division: Chromophyta

Diploneis weissflogii (A. Schmidt) Cleve Class: Dinophyceae

Diploneis littolaris (Donk.) Cleve Order: Peridiniales

Family- Cymbellaceae Family- Ceratiaceae

Amphora turgida Greg. Ceratium sp.

A. proteus Ceratium tripos (O.F.Muller)

A. laevis Greg. C. carriense Gourret

A. terroris C. fusus (Ehrenberg) Du Jardin

A. obtusa C. macroceros (Kofoid) Schiller

A.dubia Greg. C. trichoceros (Ehrenberg) Kofoid

Cymbella sp C. inflatum (Kofoid) Jorgensen

Sub-order- Bacillariineae C. karsteni Pavillard

Family – Achnanthaceae C. pavillardii Jörgensen

Bacillaria paxillifer (Mull.) Hend. C. falcatum (Kofoid) Jorgensen

Nitzschia longissima (Brebisson, in Kutzing) Ralfs in Pritchard

C.declinatum (Karsten) Jörgensen

N. sigma Kützing C. conciliens Jörgensen

N. panduriformis Gregory C. breve(Ostenfeld et Schmidt) Schroder

N. bicapitata C. furca (Ehrenberg) Clapar‘ede et Lachmann

N. closterium (Ehrenberg) W. Smith Family- Peridiniaceae

N. sigmoides (Nitzsch.) W. Smith Protoperidinium sp

N. vidovichii Protoperidinium elegans Cleve

N. incurva Protoperidinium grande (Kofoid) Balech

Protoperidinium pallidum Ostenfeld Cyanobacteria

Peridinium pentagonum (Gran) Balech Division: Cyanophyta

P. pyriforme (Paulsen) Balech Order- Oscillatoriales

Family – Pyrophacaceae Trichodesmium erythraeum Ehrenb.

Order – Gonyaulacales T. thiobautii Gomont

Pyrophacus horologium Stein Silicoflagellates

Table 5: List of phytoplankton species recorded at Kalpakkam Coast (March 2008- February 2009)


564

survival of the phytoplankton. Relatively high concentration of nitrate observed during monsoon period,

which could be attributed to the addition of nutrient rich freshwater into the coastal milieu. Moreover, land

run off and two backwater system also have some input to the coastal water during NE monsoon period. This

confirms the landward origin of nitrate. Comparatively low nitrate concentration during post monsoon/

summer may be due to heavy uptake by phytoplankton. An analogous trend was also observed by Sargunam

(1994) from this locality. Inevitably, a strong positive correlation was seen between Nitrite and nitrate. The

negative correlation between TN and chlorophyll might have indicated utilization of nitrogenous nutrients

by photosynthetic autotrophs. During the present study relatively high PO4 concentration during October/

November followed by September indicated the phenomenon of upwelling, an event that occurs during pre-

monsoon period (Aug/Sep), which might have retained till October/November in the present case. A sharp

decline in PO4 concentration during December could be due to the monsoonal dilution of seawater, because

it is believed that PO4 may be released from sediment because of turbulent action associated with strong

winds prevailed during this period (Chandran and Ramamoorthi, 1984). TP was found to be strongly associated

with PO4 as was expected and with chlo-a also a strong positive relation indicated negligible utilization by

the autotrophs. An elevated silicate concentration during monsoon period coincided with maximum influx of

backwater into the coastal water during the above period. It is believed that brackish water is rich in SiO4

concentration. This observation was strengthening from the significant negative correlation observed between

silicate and salinity.

Phytoplankton: species composition

In contrast to the present study (Total 186 species of phytoplankton), Sargunam (1994) and Poornima (2005)

had recorded only 64 (57 diatoms) and 65 (60 diatoms) species of phytoplankton from this area during their

two years of study respectively. The results of the present study thus showed almost a three fold increase in

the species composition of phytoplankton taxa as compared to earlier (Sargunam, 1994 and Poornima, 2005)

(Table 5). Some of the very common species, which are observed by us, were not observed by Sargunam

(1994). It is difficult to provide a dialectical explanation for such an abrupt increase in species number as

compared to the observation made by Sargunam (1994) and Poornima (2005) or otherwise why so less

number of species was prevailed then as compared to the present observation. It is interesting to mention

here that Sarojini and Sarma (2001) have reported 143 phytoplankton species from Andaman and Nicober

region of the Bay of Bengal in a short span of study (26th – 31st October 1996) from 5 sampling stations.

Similarly, Geeta Madhav and Kondalarao (2004) have reported 249 species from the coastal waters of BOB.

However, it would be odious to compare their results with ours, because they had collected samples from

292 stations of the BOB spreading over three years (1999-2002). In a study carried out from Gopalpur coast,

east coast of India spanning over a year, (Gouda and Panigrahy, 1996) have reported 131 species. Their

result is found to be fairly comparable with the present result with respect to the species number. However,

Rao and Sarojini (1992) have reported only 62 species of phytoplankton in the coastal waters of Andhra

Pradesh, east coast of India. Similarly, only 36 species of phytoplankton have been reported by Sawant and

Madhupratap (1996) from the west coast of India. In both these cases samples were collected from 9 stations

during cruise programme. It is well recognized that each species is a variable and, on the basis of its

relationship with other species, the patterns of assembling or grouping is established (Paul et al., 2007).

Moreover, this kind of variations could also be attributed to the taxonomic skill, technique used and availability

of literature for identification. Notwithstanding the incontestable or contestable observations of Sargunam

(1994) and Poornima (2005), two important points emerged from the present study such as, a) three fold

increase in species number is something the marine scientists should be concerned about and b) to understand

the environmental change, coastal milieu undoubtedly needs to be monitored at regular and frequent intervals

without any hiatus, because phytoplankton species number of a region is strongly associated with its local

environmental variables (Villac et al., 2008).

Presently observed high population density and species diversity during post-monsoon and pre-monsoon

season might be due to the predominance of diatoms such as Thalassiothrix frauenfeldii, Odontella sinensis,

Bacteriastrum comosum, Chaetoceros affinis, Coscinodiscus centralis, Ditylum brightwelli and Skeletonema


565

costatum. The phytoplankton abundance during post-monsoon season could be attributed to the increased

salinity, pH, high temperature and high intensity of light penetration during the season (Mani and

Krishnamurthy, 1989; Sarvanakumar et al., 2008). The abundance of phytoplankton was lowest during monsoon

months, when the water column remarkably stratified to a large extent because of heavy rainfall, high

turbidity caused by run-off, reduced salinity, decreased temperature and pH. This is being supported by Ei-

Gindy and Dorghan (1992) who stated that phytoplankton and their growth depend on several environmental

factors, which are variable in different seasons and regions.

Predominance of diatoms in phytoplankton assemblage and dominance of centrics over pennates with respect

to species number are known to be very common phenomena in coastal waters. As diatoms are larger in size

as compared to other phytoplanktonic components, their rate of sinking gets faster and floating efficiency

gets weakened. Thus, to withstand this problem, diatom always prefers to inhabit and dominates the

phytoplankton community in shallow, turbulent and upwelling region i.e. coastal region (Stowe, 1996).

Diatoms such as Asterionellopsis glacialis, Nitzschia longissima, N. sigma and Thalassionema nitzschioides

among pennales and Biddulphia mobiliensis, Chaetoceros lorenzianus, Coscinodiscus marginatus, Thalassiosira

decipiens, T. subtilis and T. eccentrica, among centrales were found to be very common during the present

observation. Similar observations have been made from different locations of east coast of India (Murrugan,

A. and Ayyakkannu, 1993; De et al., 1994; Gouda, R. and Panigrahy, 1996). In contrast to the present

observation, reports by Sargunam (1994) indicated the presence of Amphora bigibba, Nitzschia frauenfeldii

and Nitzschia closterium as common diatoms throughout his investigation. However, according to Poornima,

Amphora coffaeformis, Nitzschia closterium, N. longissima, Nitzschia sp. and Thalassionema nitzschioides

were marked as the frequently encountered species. According to Raymont (1980), the diatom species such

as, Planktoniella sol, Thalassionema nitzschioides, Chaetoceros compressus, Leptocylindrus danicus,

Skeletonema costatum and the dinoflagellate species Prorocentrum micans and Ceratium furca form typical

members of warm water phytoplankton.

Pennates predominated the plankton community during pre- and post- monsoon periods. The abundant pennate

diatoms viz., Thalassiothrix longissima, T. frauenfeldii, Navicula sp. etc (usually with high surface to

volume ratio) might be absorbing nutrients rapidly during the above periods, when optimum salinity,

temperature and nutrient conditions prevailed. However, during monsoon period, centric diatoms dominanated

over pennates. The highly diverse centric diatoms such as, Skeletonema coastatum, Coscinodiscus, Chaetoceros,

Leptocylindrus, Guinardia etc with low surface to volume ratio might begin multiplying during monsoon

period having relatively low salinity and temperature, a conducive environment for their growth.

It has observed that NH3 and TN showed a negative correlation with chlorophyll because of highly uptake

of nitrogenous nutrients by autorophs. Chlorophyll and TP were also showing positive correlation indicating

the insignificant influence of phosphate on phytoplankton growth at this area. Subramaniyan and Sen Gupta

(1965) and Gouda Panigrahy (1996) have also reported that there is not be short of of phosphate for growth of

phytoplankton along the madras coast and Gopalpur coast in the east coast of India respectively.

Phytoplankton and environmental variables

Though a positive correlation was observed between phytoplankton and temperature, but it is worth mentioning

here that temperature has not been known to have direct influence in phytoplankton apart from the Indian

coastal waters. (Gouda and Panigrahy, 1996).A positive correlation was observed between phytoplankton

and salinity which indicated its prime role in controlling the phytoplankton community structure at this

location. Due to the typical salinity condition, there was also a significant variation in population density

and no of species during the period of pre monsoon and monsoon. It has also observed from earlier reports

from (Braaud and Rossavik, 1951; Murrugan and Ayyakkannu, 1993; Gouda and Panigrahy, 1996; Devassy

and Bhattathri, 1974). The recorded low chlorophyll-a values could be due to the river water dilution which

cause turbidity and less availability and also due to anthropogenic activities as evidenced by its positive

correlation with salinity (Kawabata et al., 1993; Thillai Rajsekhar et al., 2005).

Statistical analysis


566

The results of multivariate analysis were obtained between the temporal variability in all the environmental

factors and phytoplankton aspects (Fig. 6). In total 4 groups (cluster) of period was observed. All the four

were obtained at a similarity level of 0.965. The first cluster was formed by premonsoon months (July-Sep).

The second one comprised of the post-monsoon/ Summer months (Mar-Jan). The third cluster was formed by

Oct, Jan and Feb, whereas the last group was formed by the peak monsoon months (November and December).

The above groupings coincided with the physico-chemical and biological characteristics which are petrified

by the above typical periods. The period from July- September is considered as pre-monsoon or southwest

monsoon, which is not active at this location. Thus the characteristics of coastal water quality and phytoplankton

variability were almost similar during this period as can be seen from season variations of coastal water

properties. However, the period from March-June is considered as postmonsoon/Summer, when the coastal

water property is found to be almost stable and favorable for phytoplankton growth and proliferation. The

third cluster was formed by the initial and termination period of monsoon and the initial period of post-

monsoon. In general, elevation in nitrogenous nutrients concentrations, silicate, DO and decrease in salinity

and chl-a was observed during the above period, which led to clustering of all these months together. The

last cluster was formed by the peak monsoon months (November/ December), when the above described

properties were observed very distinctly, thus Novemberand December formed a separate and clear cluster.

These observations showed that the coastal waters of Kalpakkam, in a year behave as four different water

masses, according to which phytoplankton community survives and proliferates.

Seven active principal components (PC) were identified from the PCA analysis, which altogether accounted

for 74.67% of the total variability (Table 4). PC-1 contributed 19.12% of total variability and was found to

be positively loaded with salinity, secchi disc and chlorophyll, whereas, negatively loaded with ammonia. It

explained that during the period of high salinity and good light penetration, phytoplankton growth (in terms

of chlorophyll-a) is optimal. Similarly, PC-2 and PC-3 explained the enrichment of nitrite and nitrate and

phosphate and total phosphorous in the coastal waters respectively. PC-4 showed that phytoplankton growth

was adversely effected by temperature. Enrichment of silicate during high turbidity was explained by PC-5.

PC-6 showed the positive loading of total nitrogen, whereas, an interrelation between dissolved oxygen and

phytoplankton was established in PC-7. Among all the parameters DO, secchi disc and chlorophyll-a showed

cross loading.

CONCLUSION

Of the two transects investigated, 1st transect (0.5 km) recorded more species diversity, population density

and chlorophyll-a concentration as compare to 2nd transect (4 km). A substantial increase (3 fold i.e. 60 to

186) in phytoplankton species composition has been observed as compared to the earlier reports from this

region. Very common phytoplankton species, which were not encountered earlier, were observed during the

present study. Nitrogenous nutrients were found to be limiting phytoplankton during monsoon periods, however,

the role of silicate and phosphate remained insignificant. Salinity and turbidity played a significant role in

phytoplankton species composition and density. Common and frequently observed diatoms during the present

study were agreement to the earlier findings.

ACKNOWLEDGEMENTS

The authors are thankful to the Dr. Baldevraj Director of IGCAR, for extending his help and cooperation to

carry out this task.

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