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All issues No 417 (2016) Knowl. Manag. Aquat. Ecosyst., 417 (2016) 2 Full HTML
Open Access
Issue
Knowl. Manag. Aquat. Ecosyst.
Number 417, 2016
Article Number 2
Number of page(s) 9
DOI https://doi.org/10.1051/kmae/2015034
Published online 18 January 2016

© M.B. Devi et al., published by EDP Sciences, 2016

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License CC-BY-ND (http://creativecommons.org/licenses/by-nd/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. If you remix, transform, or build upon the material, you may not distribute the modified material.

thumbnail Fig. 1

Map after showing study sites.

1 Introduction

Phytoplankton are highly diverse group of photoautotrophic organisms with chlorophyll- a and unicellular reproductive structures, which are important for aquatic habitats (Wetzel, 2001; Ariyadej et al., 2004). They are important primary producers in the base of the food chain, constitute a vital link and an important biological indicator of the water quality (Laskar and Gupta, 2013). Maintenance of a healthy aquatic ecosystem depends on the biotic properties of water and the biological diversity of the ecosystem (Harikrishnan et al., 1999). Thus study of phytoplankton is very useful tool for the assessment of water quality in any type of water body and also contributes to the understanding of basic nature and general economy of the lake (Pawar et al., 2006). Occurrence and abundance of phytoplankton species depends on the physico-chemical characteristics of water. For effective monitoring and maintenance of water quality, it is very important to know about different physico-chemical and biological characteristics of water.

The Baskandi Lake, locally known as ’Baskandi anua’ in Cachar district is formed by the meandering of the course of the River Barak (Gupta and Devi, 2014). The lake serves as habitat for diverse animals and plants. Villagers around the lake fully depend on its resources particularly fish for their livelihood and water for everyday use. Further the lake water act as source of irrigation during the dry season. Thus the lake has substantial impact on the socio-economy of the surrounding community. Increasing human habitation led to overexploitation of aquatic resources especially fish.

In Cachar district a few studies were conducted on phytoplankton and zooplankton communities of different fresh water systems (Dutta Gupta et al., 2004; Bhuiyan and Gupta, 2007; Laskar and Gupta, 2009, 2013; Das et al., 2011; Dalal and Gupta, 2013; Devi et al., 2013; Gupta and Devi, 2014). Gupta and Devi (2014) made a very preliminary study on phytoplankton and zooplankton community of Baskandi anua. But till now no detail information is available on seasonal variations in phytoplankton community of Baskandi anua, its chlorophyll content and biomass. In order to fill up this lacuna, this study was taken up to investigate phytoplankton diversity, chlorophyll content and biomass along with physiochemical properties of water of the lake in different seasons.

2 Materials and methods

Baskandi anua is situated between 24°48.615′N (latitude) and 092° 55.882′E (longitude) in Cachar district, Assam, North east India. It is lies 24.7 m above sea level. The length, breadth and area of Baskandi anua is found to be 2230 km, 2.05 km and 3920 km2 during Full storage level (FSL) (June-Sep) and 2090 km, 1.90 km and 3670 km2 at Dead storage level (DSL) (Nov-April) (Figure 1). The lake exhibits variable water level ranging from 0.25 m to 5.85 m at FSL and 0.14 m to 4.12 m at DSL. The lake is covered with Hydrilla and other macrophytes like Eichhornia, Trapa, Alternanthera, Polygonum, Ludwizia sp., etc. Phytoplankton and water samples were collected in winter (Dec, 2009−Feb, 2010), pre-monsoon (March-May, 2010), monsoon (June, 2010−August, 2010) and post- monsoon (Sep, 2010−Nov, 2010) from 5 selected sites across the lake. Physiochemical parameters such as dissolved oxygen (DO), total alkalinity (TA), pH, electrical conductivity (EC), free carbon-dioxide (FCO2), chloride (Cl), total hardness (TH), calcium (Ca+2), magnesium (Mg+ 2) and biological oxygen demand (BOD), phosphate (PO4), nitrate (NO3) and ammonium-Nitrogen (NH3-N) were analyzed by standard methods (Michael, 1984; Trivedy and Goel, 1986; APHA, 2005). Transparency (Trans) was measured by Secchi disk. Chlorophyll a, b, c and pheophytin content were determined following Abbasi (1998). By assuming that chlorophyll-a constitutes on the average 1.5% of the dry weight of algae, the biomass was estimated by multiplying the chlorophyll-a content by a factor of 67 (APHA, 2005). Trophic State Index (TSI) was also calculated following Carlson (1977).

For phytoplankton collection, 50 L of water was collected from the surface with minimal disturbance in replicate (5) and filtered in a bolting silk cloth net of mesh size 40 μm. The final volume of the filtered sample was 125 mL which was preserved by adding of 5% formalin. After 24 h, each sample was centrifuged and concentrated to 10ml with distilled water (Michael, 1984; APHA, 2005).The quantitative analysis of phytoplankton is done by Lackey’s drop method. The cover slip was placed over a drop of sample in the slide, added a pinch of glycerin and mounted it with a cover slip and was examined under microscope (APHA, 2005).

Fot Lackey’s drop method: where

  • R = Number of organisms counted per subsample.

  • At = Area of coverslip, mm2.

  • As = Area of one strip, mm2.

  • S = Number of strips counted.

  • V = Volume of sample under the coverslip, ml.

Therefore, Total organisms per liter = N × 1 /C. For qualitative analysis, phytoplankton samples were screened and various planktonic taxa belonging to each group were identified following standard books (Edmondson, 1959; Prescott, 1982; Anand, 1998). Dominance status of phytoplankton was described on the basis of relative abundance (Engelmann, 1978). Biodiversity indices such as Shannon-Wiener diversity index (H′), Buzas and Gibson’s evenness index (eH/S), and Berger Parker’s Dominance index (D) on the basis of phytoplankton abundance were computed using PAST software version 2.13 (Hammer et al., 2001). One way Analysis Of Variance was performed by using SPSS version 16. Canonical correspondence analysis (CCA) was done by using PAST software version 2.13 after logarithmic transformation of data, except for the pH data.

3 Results

Diversity, relative abundance and dominance of phytoplankton community of the Lake were studied during December 2009 to November 2010. A total of 41 phytoplankton taxa belonging to 5 classes (Cyanobacteria, Chlorophyceae, Euglenophyceae, Bacillariophyceae, and Dinophyceae) were quantified in 4 seasons (Table 1). Maximum number of phytoplankton taxa was found in pre monsoon followed by monsoon and minimum was found in post monsoon. A total of 17 species of Chlorophyceae was recorded with highest relative abundance (70.5%) in winter and lowest (8.6%) in monsoon (Table 1), 8 species of Cyanobacteria contributed highest relative abundance (66.7%) in post monsoon and lowest (26.2%) in winter while 10 species of Bacillariophyceae contributed highest relative abundance (14.8%) in post monsoon and lowest (3.3%) in winter (Table 1). Euglenophyceae population consisted of only 5 taxa having highest relative abundance (29.3%) in monsoon and lowest (16.8%) in pre monsoon (Table 1). Only one species Ceratium hirundinella belonging to Dinophyceae was recorded in pre monsoon (2.2%). According to Engelmann’s scale (1978), during the year of study, Spirogyra indica was found only eudominant species in winter. Dominant species in the lake were Lyngbya sp. in winter, Microcystis aeruginosa in pre monsoon, Euglena gracilis in pre monsoon and post monsoon, Trachelomonas sp. in monsoon, Anabaena sp. and Nostoc commune in monsoon and post monsoon and Oscillatoria sp. in post monsoon. In the present study, Shannon (H′) value was found highest during pre monsoon (1.6 ± 0.24) followed by monsoon (1.3 ± 0.75) and recorded lowest value in winter (0.8 ± 0.30). Buzas and Gibson’s evenness index (eH/S) was found to be highest in pre monsoon (0.9 ± 0.10) followed by monsoon (0.9 ± 0.13) (Table 2).The values of Chlorophyll- a concentration ranged from 14.2 μg·L-1 (pre monsoon) to 33.9 μg·L-1 (monsoon), Chl-b ranged from 2.8 μg·L-1 (pre monsoon) to 9.7 μg·L-1 (winter) and Chl-c value ranged from 0.5 μg·L-1(pre monsoon) to 15.1 μg·L-1(winter). Pheophytin values in the lake ranged from 20.1 μg·L-1 (pre monsoon) to 61.6 μg·L-1 (post monsoon). The phytoplankton biomass was highest in monsoon (2260.5 μg·L-1) (Table 3).

Table 1

Seasonal distribution, relative abundance and dominance status (Engelmann’s scale, 1978) of phytoplankton species in Baskandi anua.

Table 2

Diversity indices on the basis of phytoplankton abundance in Baskandi anua.

Table 3

Chlorophyll content and biomass of phytoplankton in Baskandi anua with one way ANOVA.

During the sampling period the study area had annual average rainfall of 255 mm with highest value in monsoon (507 mm) and lowest in winter (2 mm) (Figure 2). The pH values ranged between 5.9 (monsoon) to 7.2 (winter). The highest Trans value (36 cm) was recorded in winter and the lowest (9.9 cm) was recorded in post monsoon. BOD values of the lake ranged between 2 (monsoon) to 3.7 mg·L-1 (pre monsoon). TA values ranged between 35.1 (winter) to 52.2 mg·L-1 (monsoon). TH ranged between 42.8 to 50.4 mg·L-1 , showed highest value in monsoon and lowest in winter. Carlson’s Trophic State Index (TSI) values ranged between 63.4 (winter) to 73.2 (Post monsoon) (Table 4).

thumbnail Fig. 2

Monthly variation in rainfall data during the study period (Source: Tocklai Tea Research Station, Silchar, Assam.)

The influence of eighteen environmental variables on the distribution of phytoplankton groups in Baskandi anua are assessed using CCA (Ter Braak, 1986) (Figure 3). The eigen values of CCA axis 1 and 2 are 0.157 and 0.067 (Table 5) respectively. The CCA axis 1 and axis 2 explained 67.5% and 28.7% (Table 5) variation in the phytoplankton-environment relationships. Axis 1 is mainly associated with WT, NO3, TH and TA whereas again axis 2 is mainly associated with DO and Cl. Chlorophyceae and Bacillariophyceae lay in CCA axis 1 and Euglenophyceae also lies close to Axis 1. Cyanobacteria have been found to be grouped with monsoon and post monsoon season close to both the axis 1 and 2 toward the center. Dinophyceae recorded only in post monsoon lie close to Axis 2.

thumbnail Fig. 3

Canonical correspondence analysis (CCA) diagram of environmental variables and Phytoplankton groups in different seasons in the study area. The phytoplankton groups related to the environmental variables are presented by squares while triangles represent seasons. (WD – Water depth, WT – water temperature, AT – air temperature, EC – electrical conductivity, Trans – transparency, FCO2 – free carbon dioxide, DO-dissolved oxygen, BOD-biological oxygen demand, TA-total alkalinity, TH-Total Hardness, Ca+2 – Calcium, Mg+2 – Magnesium, Cl – chloride, NO3 – nitrate, PO4-phosphate , NH3-N – Ammonia nitrogen and RF – rainfall).

4 Discussion

A seasonal change in phytoplankton community with regard to abundance and species composition was evident in the study. Macrophytes were found abundant in the systems which have direct or indirect effect on phytoplankton density and biomass. Excess use of phosphorous and nitrogen by macrophyte reduce nutrient availability to phytoplankton (Stephen et al., 1998). Also aquatic vegetation provides shelter to zooplankton which feed upon phytoplankton and at times reduces phytoplankton densities (Irvin et al., 1990, Stephen et al., 1998). Five different phytoplankton groups (Cyanobacteria, Chlorophyceae, Euglenophyceae, Bacillariophyceae and Dinophyceae) with 41 phytoplankton taxa were quantified in 4 seasons and compared to the previous investigation made by Gupta and Devi (2014) on the same lake where they recorded 30 phytoplankton taxa belonging to Chlorophyceae, Cyanobacteria and Bacillariophyceae during 6 months collections in 2009. Borics et al. (2011) recorded 21 species in the Tiszadob oxbow of Carpathian basin, Central Europe. 47 species belonging to seven groups of phytoplankton were identified from the Rewalsar Lake, Himachal Pradesh in two consecutive years (Jindal et al., 2014). Min et al. (2011) recorded a total of 46 species in Lake Yueya (Eutrophic lake), Nanjing, China in 2006, which was reduced to 33 species and then to 21 species in the next two years.

Highest relative abundance of Cyanobacteria population than that of other groups in monsoon and post monsoon indicated eutrophic condition which is further confirmed by high nutrient content such as PO4, NO3, NH3-N in water and TSI value. This conformed to the studies made by Paramasivam and Srinivasan (1981), Maeda et al. (1992), Kumari et al. (2008), Ghosh et al. (2012). Rain water might have brought more nutrients into the lake as surface run off which enhanced the growth of phytoplankton especially Cyanobacteria and Euglenophyceae. A study in a floodplain lake of Barak Valley showed that red bloom of Euglena sp. was induced by high concentration of NH3-N, NO3, Fe, Mg and to some extend PO4, Cu, Zn in water (Dutta Gupta et al., 2004). Maximum relative abundance of Chlorophyceae recorded in winter might be due to low temperature which enhanced the growth of green algae (Tiwari and Chauhan, 2006). Spirogyra indica belonging to Chlorophyceae was the only eudominant species recorded in winter in the whole study period. Dominant species recorded in different seasons belonged to Cyanobacteria and Euglenophyceae group (Table 1). This indicated poor water quality condition as these are generally seen to appear near sewage outfall (Pandit, 2002). Greater availability of nitrates and phosphates in the rainy season might have supported dominance of blue green algae such as Microcystis sp., Lyngbya sp., Merismopedia sp. etc. as shown by Swarnalatha and Narasingrao (1993) and Ghosh et al. (2012). Ceratium hirundinella was also recorded in another oxbow lake of Cachar District (Das et al., 2011). This species is generally described as a typical species of stratified and warm water of the summer period (Wetzel, 2001) and it often dominates the summer phytoplankton in lakes (Rengefors et al., 1998).The highest Shannon (H′) value during pre monsoon followed by monsoon was due to surface runoff from nearby rice fields and human habitats during rainy seasons which made the lake nutrient rich and in turn enhanced the growth of phytoplankton. Highest H′ value for phytoplankton population in pre monsoon was also recorded in a floodplain lake of Cachar (Laskar and Gupta, 2009). Buzas and Gibson’s evenness index (eH/S) expressed the degree of uniformity in the distribution of individual among the taxa and it is found to be highest in pre monsoon followed by monsoon. This indicated that species were more evenly distributed in this lake during these seasons.

Chlorophyll content of phytoplankton indicates the physiological status of phytoplankton community and primary production of water. The Chl-a concentration in this lake can be compared with other oxbow lakes such as Atkai-Holt-Tisza (2.4−49 μg·L-1), Holt-Szamos Tunyogmatolcs (9.4−38.3 μg·L-1) and Malom-Tisza (2.3−44.9 μg·L-1) located in the Tisza valley, East Hungary (Krasznai et al., 2010) and Tiszadob oxbow (4−25 μg·L-1) of Carpathian basin, Europe (Borics et al., 2011). According to Abbasi (1998) greater ratio of pheophytin- a to chlorophyll- a indicates poor water quality and in post monsoon this ratio was found highest in the lake.

Table 4

Seasonal variations in environmental variables and Trophic State Index (TSI) of water in Baskandi anua with one way ANOVA.

Rainfall is the most important cyclic phenomena which bring variation in physico-chemical parameters of water and in turn leads to variation in distribution and diversity of aquatic communities. In this study the environmental variables were found in two different groups. Dpt, TH, Ca+2,TA, Cl, PO4 and NO3 formed one group which increased from winter to monsoon period and decreased again in post monsoon. The second group pH, EC, FCO2, Mg+2, NH3-N, and DO decreased from winter to monsoon and again increased in post monsoon (Table 4). During pre monsoon and monsoon input of sewage, drainage water and fertilizers from nearby rice field has led to the increase of TH, Ca+2, TA, Cl, PO4 and NO3. Deposition of these nutrients into water promoted growth of phytoplankton (Francis et al., 1997). The highest Trans value recorded in winter might be due to low or no disturbance in water. On the other hand Trans value was found lowest in post monsoon. Transparency can also indicate the turbidity (cloudiness) of a water body. This is influenced by algae, suspended sediments and these values again conferred trophic status of the lake. Baskandi anua water was found moderately polluted as according to Hynes (1960), BOD values between 2−7 mg·L-1 represent slightly polluted water. This is also revealed by TA values (Spence, 1964) which indicated moderately rich nutrient condition of the lake. This agreed with the earlier finding in the same lake (Gupta and Devi, 2014). Based on TH (mg·L-1) the water can be categorize into Soft (0−30), moderately soft (30−60), moderately hard (60−120), hard (120−180) and very hard (>180). Accordingly, water of this lake was soft in all the seasons while moderately soft in monsoon (50.40 mg·L-1). Carlson’s Trophic State Index (TSI) classification (Carlson, 1977) is used to provide a single trophic criterion for the purpose of classifying and ranking water bodies in complex multi-wetland systems. Carlson’s Trophic State Index (TSI) value less than 30 indicates oligotrophic condition, between 50−70 and more than 70 indicates high level of trophic status as eutrophic and hypereutrophic condition. TSI value in this lake indicated eutrophic condition in all the seasons (Carlson, 1977). This can be compared with TSI values of Hansadanga Lake, West Bengal, India (60.97-eutrophic) (Chakrabarty et al., 2010) and shallow lake of Babol city, North Iran (75.06-hypereutrophic) (Rahmati et al., 2011). Highest value of TSI in post monsoon followed by monsoon is attributed to high nutrient loading in these seasons which promoted growth of phytoplankton with higher chlorophyll- a which in turn decreased transparency. According to one way analysis of variance (ANOVA) WT, Trans, pH, EC, DO, FCO2, TA, Ca+2, Cl, NO3 and NH3-N (Table 4) had shown significant seasonal differences. This is further confirmed in the CCA diagram where rainfall had a negative relationship with variables such as pH, EC, TA, Trans, Mg+2, NH3-N and positive relationship with other variables such as Cl, Ca+2, TH, WT as well as WD (Water depth) (Figure 3).This corresponded to the findings in a reservoir-channel, in the semiarid Rio Grande do Norte State, Brazil by Câmara et al. (2009).

Table 5

Summary of canonical correspondence analysis (CCA) between phytoplankton groups and environmental variables.

In CCA analysis, the species environmental correlations for all axes are high; all of them are having a value of 1 (Table 5). Axis 1 is mainly associated with WT, NO3, TH and TA. Chlorophyceae and Bacillariophyceae lay in CCA axis 1. So according to their position in CCA diagram, increase in Chlorophyceae population is associated with increase in EC, TA, BOD and PO4 (Figure 3). Population of Euglenophyceae and Bacillariophyceae is associated with WT, TH, NO3 and RF. Again axis 2 is mainly associated with DO and Cl. The Cyanobacteria grouped with monsoon and post monsoon season is found strongly associated with DO2, FCO3, AT and NO3 Similar observations were made by Dokulil and Teubner (2000), Eynard et al., (2000) and Mischke (2003). Dinophycea is found associated positively with BOD and PO4i.e. the factors associated with input of organic matters and nutrient in the water.

5 Conclusions

This investigation found the lake Baskandi anua as eutrophic. Hence for arresting deterioration of the lake and for conserving its biodiversity appropriate remedial measures should be taken by the management as well as the inhabitants. Long term biomonitoring of water quality of the lake coupled with socio economic reviews might provide clues for identifying the sources of stress and subsequently environment awareness can be disseminated.

Acknowledgments

The authors are thankful to the Head, Dept. of Ecology and Environmental Science, Assam University, Silchar, for providing laboratory facilities. The first author is thankful to the University Grants Commission, New Delhi, India for the financial support.

References

  • Abbasi S.A., 1998. Water quality; sampling and Analysis, Discovery publishing House, New Delhi, 212 p. [Google Scholar]
  • Anand N., 1998. Indian Freshwater Microalgae, Bishen Singh Mahendra Pal Singh, Dehradun, 94 p. [Google Scholar]
  • APHA, 2005. Standard methods for examination of water and wastewater, 21st ed., APHA, AWWA, WPCF, Washington DC, USA. [Google Scholar]
  • Ariyadej C., Tansakul R., Tansakul P. andAngsupanich S., 2004. Phytoplankton diversity and its relationships to the physico-chemical environment in the Banglang Reservoir, Yala Province Songklanakarin. J. Sci. Technol., 26, 595–607. [Google Scholar]
  • Bhuiyan J.R. andGupta S., 2007. A comparative hydrobiological study of a few ponds of Barak Valley, Assam and their role as sustainable water resources. J. Environ. Biol., 28, 799–802. [PubMed] [Google Scholar]
  • Borics G., Abonyi A., Krasznai E., Varbiro G., Grigorszky I., Szabo S., Deak C. andTothmeresz B., 2011. Small-scale patchiness of the phytoplankton in a lentic oxbow. J. Plankton Res., 33, 973–981. [CrossRef] [Google Scholar]
  • Câmara FRA., Lima AKA., Rocha O. and Chellappa NT., 2009. The role of nutrient dynamics on the phytoplankton biomass (chlorophyll-a) of a reservoir-channel continuum in a semi-arid tropical region. Acta Limnol. Bras., 21, 431–439. [Google Scholar]
  • Carlson R.E., 1977. A Trophic state index for lakes. Limnol. Oceanogr., 22, 361–369. [Google Scholar]
  • Chakrabarty D., Biswas P. andDas S.K., 2010. Relative abundance of biotic communities of plankton and zoobenthos in three ox-bow lakes of Eastern India. Chinese J. Oceanol. Limnol., 28, 874–880. [CrossRef] [Google Scholar]
  • Dalal A. and Gupta S., 2013. Plankton diversity of two temple ponds of Silchar, Assam, North east India. I.J.S.N., 4, 79–83. [Google Scholar]
  • Das T., Pathak K. andDevi M.B., 2011. Phytoplankton and Zooplankton Communities of an Oxbow Lake in Barak Valley, Assam. Assam University J. Sci. Technol. Biol. Environ. Sci., 7, 67–75. [Google Scholar]
  • Devi M.B., Das T. and Gupta S., 2013. Limnological Studies of Temple Ponds in Cachar District, Assam, North East India. I.J.S.N., 2, 49–57. [Google Scholar]
  • Dokulil M.T. andTeubner K., 2000. Cyanobacterial dominance in lakes. Hydrobiologia, 438, 1–12. [CrossRef] [Google Scholar]
  • Dutta Gupta S., Gupta S. andGupta A., 2004. Euglenoid blooms in the flood plain wetlands of Barak Valley, Assam, North- Eastern India. J. Environ. Biol., 25, 369–373. [PubMed] [Google Scholar]
  • Edmondson W.T., 1959. Fresh water Biology. 2nd edition, John Wiley and sons. Inc., New York, 1248 p. [Google Scholar]
  • Engelmann HD. 1978. Untersuchungen zur Erfassung predozoogener komponenten im definierten.Okosystem. Forschungen Staatl Mus Naturkde, Gorlitz. [Google Scholar]
  • Eynard F., Mez K. andWalther J.L., 2000. Risk of cyanobacterial toxins in Riga waters. Water Res., 34, 2979–2988. [CrossRef] [Google Scholar]
  • Francis K., Shanmughavel P., Anbazhangan M. andParimelazhagan T., 1997. Investigation of pollution and its influence on the biomass of a monsoon fed freshwater pond. Pollution Res., 16, 133–137. [Google Scholar]
  • Ghosh S, Barinova S and Keshri JP., 2012. Diversity and seasonal variation of phytoplankton community in the Santragachi Lake, West Bengal, India, QScience Connect, 1–14. http://dx.doi.org/10.5339/connect.2012.3. [Google Scholar]
  • Gupta S. andDevi S.S., 2014. Ecology of Baskandi anua, an oxbow lake of South Assam, North East India. J. Environ. Biol., 35, 1101–1105. [PubMed] [Google Scholar]
  • Hammer Ø., Harper D.A.T. andRyan P.D., 2001. PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica, 4, 9 p. http://palaeo-electronica.org/2001_1/past/issue1_01.htm. [Google Scholar]
  • Harikrishnan K., Thomas S., George S., Paul Murugan R., Mundayoor S. andDas M.R., 1999. A study on the distribution and ecology of phytoplankton in the Kuttanad wetland ecosystem, Kerala. Pollution Res., 18, 261–269. [Google Scholar]
  • Hynes H.B.N., 1960. The biology of polluted waters. Liverpool University Press, Liverpool, 555 p. [Google Scholar]
  • Irvin K., Balls H. andMoss B. 1990. The entomostracan and rotifer communities associated with submersed plants in the North-folk Broad land-effects of plant biomass and species composition. Int. Revue Ges. Hydrobiol., 75, 121–141. [CrossRef] [Google Scholar]
  • Jindal R., Thakur R.K., Singh U.B. andAhluwalia A.S. 2014. Phytoplankton 0f dynamics and species diversity in a shallow eutrophic, natural mid-altitude lake in Himachal Pradesh (India): role of physicochemical factors. Chem. Ecol., 30, 328–338. [CrossRef] [Google Scholar]
  • Krasznai E., Borics, G., Varbiro G., Abonyi A., Grigorszky I., Pedisak J., Deak C. and Tothmeresz, B., 2010. Characteristics of the pelagic phytoplankton in shallow oxbows. Hydrobiologia, 639, 173–184. [CrossRef] [Google Scholar]
  • Kumari P., Dhadse S., Chaudhuri P. R . and Wate S.R ., 2008. A Biomonitoring of plankton to assess quality of water in the lakes of Nagpur city. In: Sengupta M. and Dalwani R. (eds.), Proceedings of Taal,2007: The 12’h world lake conference, Jaipur, Rajasthan, India, pp. 160–164. [Google Scholar]
  • Laskar H.S. and Gupta. 2009. Phytoplankton diversity and dynamics of Chatla floodplain lake, Barak Valley, Assam, North East India – A seasonal study. J. Environ. Biol., 30, 1007–1012. [PubMed] [Google Scholar]
  • Laskar H S. andGupta S., 2013. Phytoplankton community and limnology of Chatla floodplain wetland of Barak valley, Assam, North-East India. Knowl. Manag. Aquat. Ecosyst., 411, 06. [CrossRef] [EDP Sciences] [Google Scholar]
  • Maeda H., Kawai A. and Tilzes M., 1992. The water bloom of cyanobacteiral picoplankton in lake Biwa, Japan. Hydrobiologia, 248, 93–103. [CrossRef] [Google Scholar]
  • Michael P., 1984. Ecological Methods for Field and Laboratory Investigations, Tata McGraw-Hill Publishing Company Limited, New Delhi, 404 p. [Google Scholar]
  • Min Yao, Yan-Ling Li, Xiang-Dong Yang and Qian Liu, 2011. Three-year changes in planktonic diatom communities in a eutrophic lake in Nanjing, Jiangsu Province, China. J. Freshwater Ecol., 26, 133–141. [CrossRef] [Google Scholar]
  • Mischke U., 2003. Cyanobacteria associations in shallow polytrophic lakes: influence of environmental factors. Acta Oecologica, 24, 11–23. [CrossRef] [Google Scholar]
  • Pandit A.K., 2002. Algae as a component of Dal lake ecosystem in Kashmir Himalaya. In: Arvind Kumar (ed.), Ecology and conservation of lakes, reservoirs and rivers, A.P.H. Publishing Corporation, New Delhi. [Google Scholar]
  • Paramasivam M. andSrinivasan A., 1981. Changes in algal flora due to pollution in Cauvery river. Indian J. Environ. Health, 23, 222–238. [Google Scholar]
  • Pawar S.K., Pulle J.S. andShendge K.M., 2006. The study on phytoplankton of Pethwadaj Dam, Taluka Kandhar, District Nanded, Maharashtra. J. Aquat. Biol., 21, 1–6. [Google Scholar]
  • Prescott G.W., 1982. Algae of The Western Great Lakes Area, Ottokoeltz Science Publishers, W. Germany, 977 p. [Google Scholar]
  • Rahmati R., Pourgholam R., Najafpour S.H. andDoustdar M., 2011. Trophic Status of a Shallow Lake (North of Iran) Based on the Water Quality and the Phytoplankton Community. World Appl. Sci. J., 14, 112–120 (Special Issue of Food and Environment). [Google Scholar]
  • Rengefors K., Karlsson I. andHansson L., 1998. Algal cyst dormancy: a temporal escape from herbivory. Proc. R. Soc. Lond. B, 165, 1353–1358. [CrossRef] [Google Scholar]
  • Spence D.H.N., 1964. Macrophytic vegetations of Lochs, swamps and associated fens. In: Burnett J.H. (ed.) the vegetation of Scotland, Oliver and Boyd, Edinburgh, 306–425. [Google Scholar]
  • Stephen D., Moss B. andPhillips G., 1998. The relative importance of top down and bottom up control of phytoplankton in a shallow macrophyte dominated lake. Freshwater Biol., 39, 699–713. [CrossRef] [Google Scholar]
  • Swarnalatha N. andNarsingrao A., 1993. Ecological investigation of two lentic environments with reference to cyanobacteria and water pollution. Indian J. Microbial. Ecol., 3, 41–48. [Google Scholar]
  • Ter Braak C.J.F., 1986. Canonical correspondence analysis: a new eigen vector technique for multivariate direct gradient analysis, Ecology, 67, 1167–1179. [CrossRef] [Google Scholar]
  • Tiwari A. andChauhan S.V.S., 2006. Seasonal phytoplanktonic diversity of Kitham lake, Agra. J. Environ. Biol., 27, 35–38 . [PubMed] [Google Scholar]
  • Trivedy R.K. and Goel P.K., 1986. Chemical and biological method for water pollution studies, Environmental Publications, Karad, India. [Google Scholar]
  • Wetzel R.G., 2001. Limnology, Michigan state university C.B.S. college, Philadelphia, New York, 7653 p. [Google Scholar]

Cite this article as: M.B. Devi, S. Gupta and T. Das, 2016. Phytoplankton community of Lake Baskandi anua, Cachar District, Assam, North East India – An ecological study. Knowl. Manag. Aquat. Ecosyst., 417, 2.

All Tables

Table 1

Seasonal distribution, relative abundance and dominance status (Engelmann’s scale, 1978) of phytoplankton species in Baskandi anua.

In the text
Table 2

Diversity indices on the basis of phytoplankton abundance in Baskandi anua.

In the text
Table 3

Chlorophyll content and biomass of phytoplankton in Baskandi anua with one way ANOVA.

In the text
Table 4

Seasonal variations in environmental variables and Trophic State Index (TSI) of water in Baskandi anua with one way ANOVA.

In the text
Table 5

Summary of canonical correspondence analysis (CCA) between phytoplankton groups and environmental variables.

In the text

All Figures

thumbnail Fig. 1

Map after showing study sites.

In the text
thumbnail Fig. 2

Monthly variation in rainfall data during the study period (Source: Tocklai Tea Research Station, Silchar, Assam.)

In the text
thumbnail Fig. 3

Canonical correspondence analysis (CCA) diagram of environmental variables and Phytoplankton groups in different seasons in the study area. The phytoplankton groups related to the environmental variables are presented by squares while triangles represent seasons. (WD – Water depth, WT – water temperature, AT – air temperature, EC – electrical conductivity, Trans – transparency, FCO2 – free carbon dioxide, DO-dissolved oxygen, BOD-biological oxygen demand, TA-total alkalinity, TH-Total Hardness, Ca+2 – Calcium, Mg+2 – Magnesium, Cl – chloride, NO3 – nitrate, PO4-phosphate , NH3-N – Ammonia nitrogen and RF – rainfall).
In the text

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