Journal of Threatened Taxa | www.threatenedtaxa.org | 26 February 2022 | 14(2): 20615–20624

 

ISSN 0974-7907 (Online) | ISSN 0974-7893 (Print) 

https://doi.org/10.11609/jott.7663.14.2.20615-20624

#7663 | Received 16 September 2021 | Final received 28 December 2021 | Finally accepted 22 February 2022

 

 

Seasonal variations influencing the abundance and diversity of plankton in the Swarnamukhi River Estuary, Nellore, India

 

Krupa Ratnam 1*, V.P. Limna Mol 2, S. Venkatnarayanan 3, Dilip Kumar Jha 4, G. Dharani 5  & M. Prashanthi Devi 6*

 

1,3,4,5 Ocean Science and Technology for Islands, National Institute of Ocean Technology, Ministry of Earth Sciences, Govt. of India, Chennai, Tamil Nadu 600100, India.

2 School of Ocean Science and Technology, Kerala University of Fisheries and Ocean Studies, Panangad, Kochi, Kerala 682506, India.

1,6 Department of Environmental Science and Management, School of Environmental Sciences, Bharathidasan University, Tiruchirappalli, Tamil Nadu 620024, India.  

1 ratnamkrupa@gmail.com, 2 limnaa@gmail.com, 3 venkatnarayanan.srinivas@gmail.com, 4 dilipjhaniot@gmail.com,

5 dhara@niot.res.in, 6 prashanthidevi@gmail.com (* corresponding authors)

 

 

 

Editor: Anonymity requested.            Date of publication: 26 February 2022 (online & print)

 

Citation: Ratnam, K., V.P.L. Mol, S. Venkatnarayanan, D.K. Jha, G. Dharani & M.P. Devi (2022). Seasonal variations influencing the abundance and diversity of plankton in the Swarnamukhi River Estuary, Nellore, India. Journal of Threatened Taxa 14(2): 20615–20624. https://doi.org/10.11609/jott.7663.14.2.20615-20624

 

Copyright: © Ratnam et al 2022. Creative Commons Attribution 4.0 International License.  JoTT allows unrestricted use, reproduction, and distribution of this article in any medium by providing adequate credit to the author(s) and the source of publication.

 

Funding: The authors are grateful to the Ministry of Earth Sciences (MoES), Govt. of India, for providing funding to carry out the present study.

 

Competing interests: The authors declare no competing interests.

 

Author details: Krupa Ratnam is working as a Scientist in the National Institute of Ocean Technology, Ministry of Earth Sciences, Govt. of India, Chennai, India, involved in (ship) ballast water management, environmental impact studies, marine biofouling, etc. He has more than 23 years of research experience in coastal and estuarine systems. Presently, he is involved in the establishment of a land-based ballast water treatment test facility at Nellore, India. Limna Mol V.P. is working as Assistant Professor in Kerala University of Fisheries and Ocean Studies, Kochi, India. She is a marine biologist with a focus on marine ecological studies and biotechnological interventions towards conservation of the marine environment and sustainable utilization of marine resources.  Srinivas Venkatnarayanan worked in National Institute of Ocean Technology, Ministry of Earth Sciences, Govt. of India, Chennai, India, as a Scientist. He expertises in marine biotechnology, marine microbiology, zooplankton ecology, algae culture, larval rearing, biocides, antifouling, marine biofouling. He has more than 10 years of research experience.  Dilip Kumar Jha is working as a Scientist in National Institute of Ocean Technology, Ministry of Earth Sciences, Govt. of India, Chennai, India. He has expertise in coastal and marine ecology, pollution, geospatial modeling, the underwater study of biological resources, and conservation measures. He has about 24 years of research experience in coastal and marine modeling and management. Presently focussing on site suitability, cage development, and societal benefits through fish farming in open sea conditions along the Indian coasts. G. Dharani is working as Scientist and Head of Marine Biotechnology group in National Institute of Ocean Technology, Ministry of Earth Sciences, Govt. of India, Chennai, India. He has about 28 years of research experience in the field of marine biotechnology and plankton biology.  He has published many research articles in peer-reviewed international journals. Prashanthi Devi Marimuthu is working as Associate Professor in Bharathidasan University, Tiruchirappalli, India. She has expertise in remote sensing, geographical information system (GIS), spatial analysis, environment, Wetlands, Cluster Analysis, Biodiversity, water quality for the coastal environment. She has successfully guided many Ph.D. scholars and published many research articles in peer-reviewed international journals. She has about 25 years of research experience in the field of coastal area management.

 

Author contributions: KR—Participation in sampling, analysis, writing the original draft; VPLM—Participation in sample analysis; SV—Participation in sample analysis; DKJ—Participation in sampling, critical review, commentary or revision – including pre-or post-publication stages; GD—Coordination of the study and leadership responsibility for the research activity planning and execution; MPD—Statistical analysis of the data, guidance and mentorship.

 

Acknowledgements: We are thankful to Dr. G. A. Ramadass, the Director, NIOT, MoES, Govt. of India, Chennai, for the approvals and constant support. Thanks to Dr. R. Kirubagaran, Scientist-G (Retd.), NIOT, for his encouragement. We also thank our colleagues Dr. S. Rajaguru, Dr. S. Venkatesh, Mr. P. Sathish Kumar and Dr. Vikas Pandey and the staff and students of Department of Environmental Science and Management, School of Environmental Sciences, Bharathidasan University, Tiruchirappalli, India. Authors also thank the anonymous reviewers and editors for refining the manuscript.

 

 

Abstract: An integrated approach was used to study the seasonal influence on the abundance and diversity of phytoplankton and zooplankton in the Swarnamukhi River Estuary (SRE) and the adjacent coast covering five stations by collecting monthly samples from the years 2014 to 2017. A total of 54 phytoplankton species conforming to four families and 58 zooplankton species conforming to nine families were recorded. Phytoplankton abundance and richness were high during pre-monsoon (PRM - 56410 cells/L) followed by monsoon (MON – 42210 cells/L). A similar trend was observed in the case of zooplankton, where abundance was recorded high during PRM (124261 ind./m3) followed by MON (111579 ind./m3). Moreover, phytoplankton and zooplankton were dominated by the diatoms and copepods, respectively. Both phytoplankton and zooplankton exhibited significant temporal (F= 26.4, p <0.05) and spatial (F= 32.1, p <0.05) variations. The higher density and abundance were recorded in the inner stations compared to the open sea. The present study reveals that the SRE have a rich diversity which could be attributed to a higher nutrient influx in the inner stations. The anthropogenic discharge from the surrounding aqua farms, agricultural land, and human settlement area could cause concerns for the local flora and fauna if a proper mitigation plan is not evolved through long-term monitoring study in this coastal region.

 

Keywords: Abundance, diversity, estuary, indices, Nellore, Phytoplankton, zooplankton.

 

 

 

 

 

 

 

Introduction

          

Estuaries act as transitional zones and support the coastal economy in the form of fishing, aquaculture, transport, and tourism activities. They are also known to be highly productive ecosystems that provide shelter and breeding grounds for various marine aquatic organisms (Nybakken & Bertness 2005). Unlike salt marshes and backwaters, estuaries are complex and highly dynamic and their structure and function are influenced by anthropogenic inputs (e.g., aquaculture, agriculture, and industrial discharges) from the land and get transferred to the sea (Shenai-Tirodkar et al. 2016). Such anthropogenic activities can alter the physicochemical properties of water and immensely influence the migration, richness, distribution, diversity, and feeding of the associated marine aquatic organisms (Unanam & Akpan 2006). Plankton are aggregates of organisms (plants and animals) passively floating, drifting, or somewhat motile occurring in aquatic ecosystems (Lalli & Parsons 1993). Phytoplankton is grazed upon by zooplankton and other higher aquatic organisms (nektons) (Calbet 2008). Nutrient enrichment through, riverine inputs, and discharge from anthropogenic activities can significantly alter the phytoplankton growth and in turn affect the zooplankton grazing pressure (Berdalet et al. 1996). Therefore, plankton assemblages are usually helpful in assessing the water quality as they quickly respond to the environmental changes, hence; act as ecological indicators of an ecosystem (Hays et al. 2005; Longhurst 2007).

In the Indian scenario, most of the estuarine ecosystems are under stress due to natural and anthropogenic inputs from the surrounding environment. With the increase in nearby aquaculture, agricultural, and anthropogenic activities, the effluent discharges find their way into the nearby coastal areas which provides an advantageous environment to the organisms for proliferation.  Similar activities have been reported in the Swarnamukhi River Estuary (SRE) region, fewer studies have been carried out to assess the tidal variations (Reddi et al. 1993), hydrographic properties of water (Sreenivasulu et al. 2015), contamination studies on the presence of heavy metal in seawater, sediments, & organisms (Reddy et al. 2016; Sreenivasulu et al. 2018; Jha et al. 2019), and the benthic organisms (Pandey et al. 2021). However, an elaborate study for the plankton communities is not available for the SRE region. A long-term study (2014–2017) was conducted to analyze the planktonic (phytoplankton and zooplankton) assemblages. This study can serve as baseline information for future ecological assessment related to the SRE and other similar tropical ecosystems.

 

 

Materials and methods

 

Study area

The SRE region (14.072–14.077 °N and 80.126– 80.154 °E), situated in the Vakadu Mandal of Nellore district, Andhra Pradesh. This estuarine runs about 1.5 km in length perpendicular to the Bay of Bengal with an average depth of 1.0 m and an area of 6.25 km2 (Reddi et al. 1993). Nellore receives the majority of the rainfall during the north-east monsoon (October to December) than the south-east monsoon (Kannan et al. 2016). Altogether, five sampling stations were fixed; four stations covering SRE and a reference station in the open sea (OS) about a kilometer from the shore. The coordinates were fixed using GPS (Garmin) covering the study area and the surrounding coast. The selected sampling stations are shown in (Figure 1), covering the Buckingham canal (BC), near to (SR1), away from mouth (SR2), mouth (SRM), and open sea (OS). The monthly sampling was carried out covering low and high tides at all the stations. The data was categorized seasonally as pre-monsoon [PRM (January–May)], monsoon [MON (June–September)], and post-monsoon [POM (October–December)] from May 2014 to December 2017 for analysis (5 stations × 43 months × 2 tides = 430 samples).

 

Temperature and rainfall

The temperature and rainfall data for the sampling period were obtained from the Indian Meteorological Department, Ministry of Earth Sciences, Government of India. The obtained data (monthly) was plotted for better interpretation (refer to Figure 2).

 

Biological parameters

For phytoplankton sampling, 5.0 L of surface seawater samples (in triplicate) were collected in a polyethylene container and preserved with 4% formalin and Lugol’s iodine. Phytoplankton analysis was carried out using Utermöhl (1931) sedimentation technique. The samples were allowed to settle in a measuring cylinder for a period of 48 hours and siphoned (using a 10 µ mesh) to obtain 50 mL concentrate (Hasle,1978). For phytoplankton enumeration, 1 mL of the concentrated sample was taken onto a Sedgewick rafter plankton counting chamber and the total number of organisms was examined under a compound microscope. Phytoplankton was identified using standard identification keys (Subrahmanyan 1946, 1959; Santhanam et al. 1987; Tomas 1997). For chlorophyll-a (chl-a) analysis, 1,000 mL of the water sample was filtered through Whatman GF/F filter paper and chl-a, was extracted by following the modified acetone extraction method (Parson et al. 1984). The extracted chl-a samples were analyzed using a spectrofluorometer (make Hitachi model F-4600) and obtained results were expressed in mg/m3. The surface zooplankton samples were collected using a zooplankton net (150 μm mesh size, 0.5 m diameter, 1.8 m length) fitted with a digital flow meter (make Hydro-Bios). The surface hauls were made from the stern side of the boat running at a speed of 1 km/hr and the collected plankton was transferred to 500 mL polythene containers and preserved using 5% buffered formalin. In the laboratory, triplicate subsamples were taken onto a Sedgewick rafter plankton counting chamber and the total numbers of organisms were enumerated under the compound microscope (Nikon model SMZ 1500). The zooplankton was identified following the standard identification key of Kasturirangan (1963) and Santhanam & Srinivasan (1994). The zooplankton biomass was determined by the settled volume method, where the collected sample was allowed to settle and the obtained biomass was expressed as mL/m3.

 

Statistical analysis

PRIMER v6.1 was used for univariate indices, e.g., species richness (S), abundance, Margalef’s diversity (d), Shannon-Wiener diversity index (H′, log2), Simpson’s diversity (1-λ), and Pielou’s evenness (J′) (Clarke & Gorley 2006). The sitewise variation between the environmental parameters were analyzed using one way analysis of variance (ANOVA) in Microsoft Excel 2007.  To determine the phytoplankton diversity and dominance in different seasons and the stations, univariate diversity indices were applied. The abundance of phytoplankton and zooplankton was represented using a box plot using SPSS v10 software.

 

 

Results and Discussion

 

Temperature and rainfall

The rainfall data were analyzed for the years 2014–2017 and it indicates that maximum rainfall was recorded from September to December (Figure 2). It ranged 6.2–221.1 mm (2014), 8.0–767.2 mm (2015), 10.6–149.0 mm (2016), and 1.1–218.0 mm (2017). Maximum rainfall of 767.2 mm was recorded in November 2015. The lowest rainfall was recorded in 2016 during the north-east monsoon (December 149.0 mm). The atmospheric temperature (AT) ranged 22.1–40.2 °C, 21.4–39.7 °C, 22.0–39.5 °C, and 21.8–40.9 °C in 2014, 2015, 2016, and 2017, respectively. The AT peaked during the summer, i.e., April and May. The SRE region is continuously fed with tidal water and keeps the ecosystem comparatively in good condition; however, every year during the MON when the precipitation is less, the mouth of the river gets closed for a few months (Sreenivasulu et al. 2016; Pandey et al. 2021). During this period, the concentration of some of the parameters changed drastically due to stagnation. It has been reported that the rainfall can significantly affect the phytoplankton composition in the river (Jeong et al. 2007), estuaries (D’silva et al. 2012), and reservoirs (Zhou et al.,2012) worldwide.

 

Phytoplankton diversity, density, and chlorophyll-a

A total of 54 phytoplankton species include 38 diatoms, nine dinoflagellates, three green algae, and four blue-green algae. Diatoms (Bacillariophyceae) were the dominant group consisting of 70%, 69%, and 76% in PRM, MON, and POM, respectively. The next dominant was dinoflagellates (dinophyceae) registering 20%, 14%, and 18%, in PRM, MON, and POM, respectively. Green algae (Cyanophyceae) were recorded during PRM (6%) and MON (7%) seasons. Blue-green algae (Chlorophyceae) were 4%, 10, and 6%, in PRM, MON, and POM, respectively (Figure 3).

During the study period, the highest phytoplankton density was recorded in the SRM (56,410 cells/L) and it was lowest in the OS (2,440 cells/L). Phytoplankton density in the inner riverside stations, BC, SR2, and SR1 ranged 9,605–50,160 cells/L, 7,785–56,340 cells/L, and 10,500–55,850 cells/L, respectively. In SRM and OS, phytoplankton density ranged 10,033–56,410 cells/L and 2,440–37,100 cells/L, respectively. The mean phytoplankton density recorded in the inner stations BC, SR2, and SR1 were 19,785, 21,005, and 18,815 cells/L, respectively (Figure 4a). In the SRM and OS region, the mean phytoplankton density was 20000 and 17864 cells/L, respectively. The maximum density recorded in PRM, MON, and POM was 56,410, 42,210, and 24,480 cells/L, respectively. The phytoplankton density in PRM ranged 13,647–23,217 cells/L, in MON it ranged 18,585–22,746 cells/L, and in POM it ranged 9,492–16,973 cells/L (Figure 4a). Among diatoms, Rhizosolenia sp. was the dominant species in all the stations, followed by Thalassiosira subtilis and Navicula sp. The Protoperidinium sp. dominated the dinoflagellates community followed by Ceratium sp. and Prorocentrum sp. during the study period. All the three species of green algae (Chlorella sp., Oocystis sp., and Pediastrum sp.) were present during MON, while only Chlorella sp. and Oocystis sp. were represented during PRM and none of the three species mentioned above were present during POM. Among the four blue-green algae recorded during the study, Trichodesmium sp. and Spirulina sp. were observed during PRM, Microcystis sp. and Oscillatoria sp. were observed during POM, and all the four species were present during the MON. The SRE received precipitation during the POM (north-east monsoon) which could enhance the land-driven run-off from the aqua farms, agricultural land, and domestic discharge which consequently could have attributed higher nutrient inputs helping phytoplankton to proliferate and bloom. Higher phytoplankton density in the inner stations could be attributed to higher nutrient input in those stations from the surrounding regions (aquaculture runoff) (Mckee et al. 2000; Roberts & Prince 2010).

The chl-a in PRM ranged 2.11 ± 0.12 mg/m3 (OS & SRM)–10.71 ± 2.08 mg/m3 (BC). In MON, it ranged 2.10 ± 0.49 mg/m3 (OS)–8.46 ± 1.76 mg/m3 (BC). In POM, it ranged 0.78 ± 0.17 mg/m3 (SRM)–3.41±0.24 mg/m3 (BC) (Figure 4b).  The data indicates that the phytoplankton exhibited significant variations between seasons (F= 26.4, p <0.05), while variation was insignificant between the stations (F= 1.026, p >0.05). The diversity indices between the five stations did not vary significantly (F= 1.026, p >0.05). An increase in phytoplankton abundance and chl-a was on par with previous studies observed during the PRM and MON (Achary et al. 2014; Baliarsingh et al. 2016).

Univariate diversity indices have shown variations between the three different seasons (Table 1). Throughout the study, maximum phytoplankton species were recorded in the BC station in the monsoon (45 species). Marglef’s species richness (d) was the highest in MON, followed by PRM whereas it was lowest in POM. This could be attributed to the high species diversity in MON compared to the other two seasons. Pielou’s evenness (J’) and Simpson’s dominance (D) were relatively higher in the PRM and POM compared to the MON season. The relatively low value in MON can be attributed to the high species diversity during this season. In general, the high species dominance in PRM and POM can be related to the low species richness in these seasons. The maximum phytoplankton abundance and chl-a biomass were recorded during the PRM followed by MON season. The highest phytoplankton abundance and biomass was recorded during 2014 and 2015.

 

Zooplankton density and diversity

A total of 58 different species of zooplankton conforming to nine different phyla, i.e., Sarcomastigophora, Ciliophora, Ctenophora, Cnidaria, Chordata, Chaetognatha, and Arthropoda were recorded. The increased diversity of zooplankton especially the copepods observed in the estuarine region was on par with previous reports from the east coast of India (Madhupratap et al. 1992; Thippeswamy & Malathi 2009). However, the number of copepod taxa reported during the present survey was comparatively less than previous reports in the Andhra coast (Rakhesh et al. 2006).

In BC, density varied 2,722–82,540 ind./m3. In SR1, it varied 2,871–84,230 ind./m3. In SR2, the density of zooplankton varied 1,645–105,558 ind./m3. In SRM, it varied 7,551–131,579 ind./m3. Similarly, in OS, it varied 1,523–96,872 ind./m3. It was observed that zooplankton density was maximum at SRM (131,579 ind./m3) (Figure 5a). Zooplankton density in PRM, MON, and POM ranged 20,090–29,114 ind./m3, 16,390–24,330 ind./m3, and 13,286–22,426 ind./m3, respectively. Maximum zooplankton abundance was observed during PRM followed by MON and POM during the study period. The OS recorded the least abundance throughout the seasons (PRM: 20,091 ind./m3, MON: 16,390 ind./m3 & POM: 13,286 ind./m3, respectively). Maximum zooplankton biomass was observed in SR2 ranging from 0.04 to 0.13 ml/m3 throughout the study period (Figure 5b). OS recorded the least biomass (0.02 to 0.04 ml/m3) throughout the sampling period. Overall PRM followed by MON season exhibited favourable conditions for zooplankton growth in the SRE region.

Zooplankton exhibited a typical season-specific and site-specific variation. Copepods followed by invertebrate larval forms dominated the zooplankton community during all three seasons. A total of 37 species of copepods were recorded during the survey, with the major species being Acartia danae, A. spinicauda, A. clausii, Paracalanus parvus, Acrocalanus gibber, A. longicornis, Corycaeus danae, C. catus, Oithona rigida, and Euterpina acutifrons were recorded throughout the year irrespective of seasons. Copepods followed by larval forms dominate the entire zooplankton community irrespective of seasons (Figure 6). The least contributing groups (less than 10%) include organisms belonging to phyla/group Sarcomastigophora, Ciliophora, Ctenophora, Cnidaria, Chordata, Chaetognatha, and Annelida. Copepods species such as Eucalanus sp., Subeucalanus sp., Onacaea sp., Centropages sp., and Copilia sp. were present only during POM season in higher numbers in all stations which correlates with the lowering salinity in all stations due to the north-east monsoon. Apart from the copepods, some other larval forms exhibited seasonality such as bivalve (PRM and MON) and gastropod veligers (MON and POM). Larval forms belonging to phylum Mollusca, e.g., Creisis sp. and the Ophiothrix larva were exclusively present only in monsoon. Copepod nauplius, crustacean nauplius, and polychaete larvae were present throughout the year in all the stations.

Univariate diversity indices have shown variations between the three seasons (Table 2). Marglef’s species richness (d) was the highest in MON, followed by PRM and POM. Among the five stations, a significant difference in the diversity indices was observed during the POM. BC region was more diverse and recorded maximum zooplankton species (19–23). This could be attributed to anthropogenic activities in the surrounding environment (Pandey et al. 2021).

The zooplankton community exhibited significant differences between the seasons (F= 191.1, p <0.001) as well as the stations (F= 224.5, p <0.001). The present investigation has shown the presence of discrete assemblages of zooplankton communities observed in the SRE and coastal region indicating a strong seasonal fluctuation with lower abundances in POM and higher during the PRM and MON season. A similar study conducted elsewhere suggested that phytoplankton abundance plays a very important role in regulating zooplankton population in estuaries (Jagadeesan et al. 2013; Nandy & Mandal 2020).

The coast is prone to heavy rainfall, the likely discharges from the nearby aquaculture activities in the inner stations (BC, SR2, and SR1) of the SRE region which was supported with previous studies (Sreenivasulu et al. 2018).  The results of this study are in agreement with Jha et al. (2019) and Pandey et al. (2021) in the same region.

 

 

Conclusion

 

The present long-term study reveals the spatial and temporal variations of phytoplankton and zooplankton in the SRE and the adjoining coast. The study also highlights that the SRE region receives very little rainfall during the MON period and most of the rainfall occurred only during the POM period, i.e., during the north-east monsoon (NEM) period. The SRE region is known to have a good cover of mangroves swamps and is usually impacted by anthropogenic activities, such as, aquaculture farms, agriculture activities, and discharge areas from nearby vicinity. The increased nutrient concentration significantly affected the plankton community in the SRE region. Our study indicates that the phytoplankton community exhibited significant variations between seasons. The zooplankton density also showed significant variation and revealed the anthropogenic impact in the study. The present study suggests that phytoplankton and zooplankton are important indicators of a healthy ecosystem which was evident in the present study. Moreover, the study also suggests that a long-term monitoring could help in understanding the ecosystem and planning the mitigation management strategy for the tropical coastal environment.

 

 

Table 1. Spatio-temporal univariate diversity indices for phytoplankton.

Season

Station

Total species (S)

Total Individuals (N)

Marglef’s species richness (d)

Pielou’s evenness (J')

 

Shannon Wiener Diversity index (H')

Simpson’s dominance (D)

 

PRM

BC

36

23217

3.27

0.93

3.36

0.96

SR2

35

22493

3.13

0.91

3.25

0.94

SR1

36

18980

3.26

0.93

3.35

0.95

SRM

35

21054

3.16

0.93

3.34

0.95

OS

35

13647

3.28

0.91

3.25

0.95

MON

BC

45

22746

4.54

0.71

2.70

0.87

SR2

40

22409

3.99

0.73

2.72

0.87

SR1

41

18585

4.15

0.73

2.71

0.88

SRM

42

20040

4.12

0.82

3.09

0.93

OS

41

18906

3.90

0.78

2.90

0.91

POM

BC

30

14959

3.05

0.88

2.99

0.93

SR2

27

16378

2.75

0.92

3.05

0.94

SR1

29

10521

3.03

0.92

3.11

0.94

SRM

29

16973

2.94

0.91

3.07

0.94

OS

18

9492

1.87

0.91

2.64

0.90

 

 

Table 2. Spatio-temporal univariate diversity indices for zooplankton.

Season

Station

Total species (S)

Total Individuals (N)

Marglef’s species richness (d)

 

Pielou’s evenness (J')

 

Shannon Wiener Diversity index (H')

Simpson’s dominance (D)

 

PRM

BC

19

27100

1.759

0.7223

2.13

0.8415

SR2

19

27793

1.828

0.7863

2.32

0.8749

SR1

19

26655

1.874

0.7829

2.31

0.8615

SRM

19

29114

1.827

0.7811

2.30

0.8694

OS

19

20090

1.873

0.7468

2.20

0.8447

MON

BC

23

24006

2.306

0.7836

2.46

0.8493

SR2

21

16390

2.057

0.7903

2.41

0.8460

SR1

19

24330

1.932

0.7172

2.11

0.7880

SRM

22

21521

2.019

0.6835

2.11

0.8170

OS

19

16691

1.793

0.5965

1.76

0.6701

POM

BC

16

16576

1.463

0.5105

1.42

0.5485

SR2

9

22426

0.714

0.2415

0.53

0.2313

SR1

8

14828

0.783

0.6151

1.28

0.6249

SRM

14

19619

1.184

0.4009

1.06

0.4726

OS

13

13286

1.045

0.3664

0.94

0.3983

 

 

For figures - - click here

 

 

References

 

Achary, M.S., S. Panigrahi, K.K. Satpathy, G. Sahu, A.K. Mohanty, M. Selvanayagam & R.C. Panigrahy (2014). Nutrient dynamics and seasonal variation of phytoplankton assemblages in the coastal waters of southwest Bay of Bengal. Environmental Monitoring and Assessment 186: 5681–5695.

Baliarsingh, S.K., S. Srichandan, A. A. Lotliker, K. C. Sahu & T. Srinivasa Kumar (2016). Phytoplankton community structure in local water types at a coastal site in north-western Bay of Bengal. Environmental Monitoring and Assessment 188: 427. https://doi.org/10.1007/s10661-016-5424-y

Berdalet, E., C. Marrase, M. Estrada, L. Arin, & M. Maclean (1996). Microbial community responses to nitrogen and phosphorus deficient nutrient inputs: Microplankton dynamics and biochemical characterization. Journal of Plankton Research 18(9): 1627–1641.

Calbet, A. (2008). The trophic roles of microzooplankton in marine systems. ICES Journal of Marine Science 65: 325–331.

Clarke, K & R.N. Gorley (2006). Primer v6: User Manual/Tutorial.

Dash, S., S. Padhan, G. Rajhans, P. Mohapatra, R. Sarangi, D. Raut, B. Mohanty, S. Nayak & L. Patnaik (2019). Abundance and Diversity of Plankton in the Coastal Waters of Chandipur, Bay of Bengal. Russian Journal of Marine Biology 45: 252–261.

D’Silva, M.S., A.C. Anil, R.K. Naik & P.M. D’Costa (2012). Algal blooms: a perspective from the coasts of India. Natural Hazards 63: 1225–1253.

Hasle, G.R. (1978). The inverted-microscope method, pp. 88–96. In: Sournia, A. (eds.). Phytoplankton Manual 6. UNESCO Monographs on Oceanographic Methodology.

Hays, G.C., A.J. Richardson & C. Robinson (2005). Climate change and marine plankton. Trends in Ecology and Evolution 20: 337–344.

Jagadeesan, L., R. Jyothibabu, A. Anjusha, P.M. Arya, K.R. Muraleedharan & K. Sudheesh (2013). Ocean currents structuring the mesozooplankton in the Gulf of Mannar and Palk Bay, southeast coast of India. Progress in Oceanography 110: 27–48.

Jeong, K.S., D.K. Kim, & G.J. Joo (2007). Delayed influence of dam storage and discharge on the determination of seasonal proliferations of Microcystis aeruginosa and Stephanodiscus hantzschii in a regulated river system of the lower Nakdong River (South Korea). Water Research 41: 1269–1279.

Jha, D.K., K. Ratnam, S. Rajaguru, G. Dharani, M.P. Devi & R. Kirubagaran (2019). Evaluation of trace metals in seawater, sediments, and bivalves of Nellore, southeast coast of India, by using multivariate and ecological tool. Marine Pollution Bulletin 146: 1–10.

Jutla, A., S. Akanda & S. Islam (2009). Relationship between Phytoplankton, Sea Surface Temperature and River Discharge in Bay of Bengal. Geophysical Research Abstracts 11, EGU2009-1091-2, 2009, EGU General Assembly 2009.

Kannan, R., M.V. Ramanamurthy & A. Kanungo (2016). Shoreline Change Monitoring in Nellore Coast at East Coast Andhra Pradesh District Using Remote Sensing and GIS. Journal of Fisheries & Livestock Production 4: 161. https://doi.org/10.4172/2332-2608.1000161

Kasturirangan, L.R. (1963). A key for the identification of the more common planktonic Copepoda of Indian coastal waters. Publication no.2, Indian National Committee on Oceanic Research. CSIR, New Delhi.

Lalli, C & T. Parsons (1993). Biological Oceanography: An Introduction. Butterworth-Heinemann. 

Longhurst, A.R. (2007). Ecological geography of the sea. Amsterdam: Elsevier, 542pp.

Madhupratap, M., P. Haridas, N. Ramaiah & C.T. Achuthankutty (1992). Zooplankton of the southwest coast of India: Abundance, composition, temporal and spatial variability in 1987. In B.N. Desai (eds.). Oceanography of the Indian Ocean. Oxford and IBH, New Delhi, 99pp.

Mckee, L.J., B.D. Eyre & S. Hossain (2000). Transport and retention of nitrogen and phosphorus in the sub-tropical Richmond River estuary, Australia - A budget approach. Biogeochemistry 50: 241–278.

Nandy, T & S. Mandal (2020). Unravelling the spatio-temporal variation of zooplankton community from the river Matla in the Sundarbans Estuarine System, India. Oceanologia 62 (3): 326–346.

Nybakken, J.W. & M.D. Bertness (2005). Estuaries and salt marshes. In J.W. Nybakken & M. D. Bertness (eds.). Marine biology: an ecological approach. Pearson/Benjamin Cummings, San Francisco, 579pp.

Pandey, V., S. Venkatnarayanan, P.S. Kumar, R. Krupa, D.K. Jha, S. Rajaguru & G. Dharani (2021). Assessment of ecological health of Swarnamukhi river estuary, southeast coast of India, through AMBI indices and multivariate tools. Marine Pollution Bulletin 164: 112031. https://doi.org/10.1016/j.marpolbul.2021.112031

Parsons, T.R., Y. Maita & C.M. Lalli (1984). A Manual of Chemical and Biological Methods for Seawater Analysis. Pergamon Press, Oxford, 173 pp.

Rakhesh, M., A. Raman & D. Sudarsan (2006). Discriminating zooplankton assemblages in neritic and oceanic waters: A case for the northeast coast of India, Bay of Bengal. Marine Environmental Research 61(1): 93-109.

Reddi, K.R., N. Jayaraju, I. Suriyakumar & K. Sreenivas (1968). Tidal fluctuation in relation to certain physio-chemical parameters in Swarnamukhi river estuary, East coast of India. Indian Journal of Geo-Marine Sciences 22: 232–234.

Reddy, S.R., B.C., N. Jayaraju, G. Sreenivasulu, U. Suresh & A.N. Reddy (2016). Heavy metal pollution monitoring with foraminifera in the estuaries of Nellore coast, East coast of India. Marine Pollution Bulletin 113(1-2): 542–551. https://doi.org/10.1016/j. marpolbul.2016.08.051   

Roberts, A.D. & S.D. Prince (2010). Effects of urban and non-urban land cover on nitrogen and phosphorus runoff to Chesapeake Bay. Ecological indicators 10 (2): 459-474.

Santhanam, R., N. Ramanathan, K.V. Venkataramanuja, & G. Jegathee-san (1987). Phytoplankton of the Indian Seas: An Aspect of marine Botany. Daya Publishing House, Delhi, 127 pp.

Santhanam, R. & A. Srinivasan (1994). A manual of marine zooplankton. Oxford & IBH Publishing Company, 160pp.

Shenai-Tirodkar, P.S., M.U. Gauns & Z.A. Ansari (2016). Evaluation of surface water and sediment quality in Chicalim Bay, Nerul Creek, and Chapora Bay from Goa coast, India– a statistical approach. Environmental Monitoring and Assessment 188(8): 472. https://doi.org/10.1007/s10661- 016-5445-6  

Sreenivasulu, G., N. Jayaraju, B.C.S.R. Reddy & T.L. Prasad (2015). Physico-chemical parameters of coastal water from Tupilipalem coast, Southeast coast of India. Journal of coastal sciences 2(2): 34–39.

Sreenivasulu, G., N. Jayaraju, B.C.S.R. Reddy, T.L. Prasad, B. Lakshmanna, K. Nagalakshmi & M. Prashanth, (2016). River mouth dynamics of Swarnamukhi estuary, Nellore coast, southeast coast of India. Geodesy and Geodynamics 7(6): 387 - 395. https://doi.org/10.1016/j.geog.2016.09.003

Sreenivasulu, G., N. Jayaraju, B.C.S.R. Reddy, B. Lakshmanna & T.L. Prasad (2018). Influence of coastal morphology on the distribution of heavy metals in the coastal waters of Tupilipalem coast, Southeast coast of India. Remote Sensing Applications: Society and Environment 10: 190–197. https://doi.org/10.1016/j.rsase.2018.04.003    

Subrahmanyan, R., (1946). A systematic account of the marine plankton diatoms of the Madras coast. Proceedings of the Indian Academy of Sciences-Section B, 24(4):  pp 85–197.

Subrahmanyan, R., (1959). Studies on the phytoplankton of the west coast of India. parts I and II. Proceedings of the Indian Academy of Sciences, 50B: pp 113–187.

Thippeswamy, S. & S. Malathi (2009). Plankton Diversity in Indian Estuaries – A review. In: Plankton dynamics of Indian waters, pp. 306-333, edited by B. B. Hosetti, Daya Publishing House, Jaipur, India

Tomas, C.R., (1997). Identifying Marine Phytoplankton: San Diego. Academic Press, California.

Unanam, A.E. & A.W. Akpan (2006). Analysis of physico-chemical characteristics of some freshwater bodies in Essien Udim Local Government area of Akwa Ibom State, Nigeria, In: Proceeding of the 21st Annual Conference of the Fisheries Society of Nigeria.

Utermöhl, von H. (1931). Neue Wege in der quantitativen Erfassung des Planktons. (Mit besondere Beriicksichtigung des Ultraplanktons) Mit 4 Abbildungen im Text. Internationale Vereinigung für theoretische und angewandte Limnologie: Verhandlungen 5(2): 567–596.

Zhou, G., X. Zhao, Y. Bi & Z. Hu (2012). Effects of rainfall on spring phytoplankton community structure in Xiangxi Bay of the Three-Gorges Reservoir, China. Fresenius Environmental Bulletin 21: 3533-3541.