Environ Monit Assess (2015) 187:47 DOI 10.1007/s10661-014-4212-9
Spatiotemporal distribution and composition of phytoplankton assemblages in a coastal tropical lagoon: Chilika, India Suchismita Srichandan & Ji Yoon Kim & Punyasloke Bhadury & Saroja K. Barik & Pradipta R. Muduli & Rabindro N. Samal & Ajit K. Pattnaik & Gurdeep Rastogi Received: 31 July 2014 / Accepted: 1 December 2014 # Springer International Publishing Switzerland 2015
Abstract The Asia’s largest lagoon, Chilika, is a shallow water estuary and a designated “Ramsar” site located in the east coast of India. The spatiotemporal diversity of phytoplankton based on the monthly sampling between July 2011 and June 2012 was investigated in relation to physicochemical variables of the surface water column from 13 stations. The salinity was minimum (average 9) during the monsoon which was primarily due to riverine discharge. As the season progressed towards post-monsoon, average salinity of the whole lagoon reached to 10 which further increased to 20 during pre-monsoon season. A total of 259 species of phytoplankton, mostly dominated by the
Electronic supplementary material The online version of this article (doi:10.1007/s10661-014-4212-9) contains supplementary material, which is available to authorized users.
Bacillariophyta (138 species) followed by Dinophyta (38 species), Chlorophyta (32 species), Cyanophyta (29 species), Euglenophyta (18 species), and Chrysophyta (4 species), were recorded in this study. Different ecological sectors of the lagoon (except the northern sector) were dominated by diatoms, while the northern sector due to its freshwater regime supported large population of euglenoids. Based on the multivariate ordination analysis, salinity regime and light availability played important role in determining the distribution, diversity, and composition of phytoplankton communities. Overall, this study documented a very high diversity of phytoplankton and highlighted the importance of taking extensive sampling in getting a clearer understanding of phytoplankton community structure in less-studied environments such as Chilika lagoon.
S. Srichandan : S. K. Barik : P. R. Muduli : R. N. Samal : A. K. Pattnaik : G. Rastogi (*) Wetland Research and Training Centre, Chilika Development Authority, Barkul, Balugaon, Odisha 752030, India e-mail: [email protected]
Keywords Phytoplankton . Monsoon . Salinity . Spatiotemporal . Estuary
J. Y. Kim Department of Integrated Biological Science, Pusan National University, Pusan, South Korea
Coastal lagoons are highly productive ecosystems providing a range of ecological services related to the supply of food and fodder, protection from floods, groundwater recharge, and sequestration of contaminants. These ecosystems are under intense anthropogenic pressure as they receive pollutants and nutrients from the surrounding watershed community and are liable to become eutrophic (McGlathery et al. 2007; Dube and
P. Bhadury Integrative Taxonomy and Microbial Ecology Research Group, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
Introduction
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Jayaraman 2008). Due to the simultaneous connectivity with rivers and sea, coastal lagoons represent a transition zone where freshwater and marine ecosystems are linked to each other. The mixing of nutrient-rich turbid river discharge with the nutrient-poor marine water generates a continuous gradient of salinity, nutrient, and other environmental gradients which has a strong impact on the spatial and temporal distribution of phytoplankton communities. Phytoplankton being the primary producers in the lagoon ecosystem have a crucial role in the nutrient cycling as well as balancing the overall food web dynamics (e.g., Dannielsdottir et al. 2007). In addition to ensuring ecological services, phytoplankton species composition is considered an efficient bio-indicator of water quality as their distribution strongly correlates with various physical, chemical, biological, and hydrological factors as well as interactions among them (Paerl et al. 2010). These complex environmental gradients also show dynamic seasonal variation. Thus, study of spatial and temporal changes in phytoplankton communities with respect to the environmental variables is important to assess the water quality and getting a clearer understanding of net ecosystem production in the lagoon. Considering the ecological significance of phytoplankton, numerous studies have targeted phytoplankton communities in the freshwater (e.g., Stomp et al. 2011; Tian et al. 2013), marine (e.g., Cermeno et al. 2013; Edwards et al. 2013), and estuarine ecosystems (e.g., Brogueira et al. 2007; Paerl et al. 2010). These studies have provided several interesting mechanistic insights on the community assemblage, functional traits, and the seasonal dynamics of phytoplankton communities in relation to environmental gradients. Stomp et al. (2011) examined the freshwater phytoplankton diversity in 540 lagoons and observed that local environmental factors were the major drivers of phytoplankton species composition. For instance, water color, phosphorous, and alkalinity were the major environmental factors for controlling phytoplankton species composition in European lakes (Maileht et al. 2013), while ammonium and phosphorus played an important role in case of freshwater lake ecosystems from China (Tian et al. 2013). Estuarine and coastal tropical ecosystems are more challenging when it comes to determining environmental drivers of phytoplankton community. This is due to their highly dynamic nature with respect to the
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hydrology, nutrient cycling, and biotic factors. Different studies suggest that multiple environmental factors along with the site-specific factors best correlate with variation in phytoplankton communities in many tropical estuaries. For instance, salinity and turbidity were the principal factors which explained the seasonal and geographical variation in Chlorophyta, Euglenophyta, and Cyanophyta in a tropical inland freshwater estuary of southern Thailand (Lueangthuwapranit et al. 2011). Site-specific factors, e.g., heavy metals, together with salinity played an important role in structuring phytoplankton composition in a tropical coastal estuary of Vietnam (RochelleNewall et al. 2011). While other factors such as temperature, silicate, and phosphorus along with salinity controlled the phytoplankton species composition and distribution in Tagus estuary, Portugal (Brogueira et al. 2007). The Chilika is the largest brackish water lagoon in Asia located in the Odisha state along the east coast of India (19° 28′–19° 54′ N and 85° 06′–85° 35′ E) (Fig. 1). The lagoon is well known for socioeconomics, biodiversity, ecological services, and is a designated “Ramsar site-wetland of international importance.” The detailed description of this ideal lagoon ecosystem in relation to hydrology, geomorphology, and biodiversity is described elsewhere (Sahu et al. 2014). The shallow depth of lagoon (average ~2 m) allows sunlight to penetrate mostly to the bottom, supporting a high diversity of planktonic communities, benthic organisms, and aquatic macrophytes. Freshwater inflow is mostly from the 12 major rivers which together forms the catchment basin of the lagoon. The lagoon covers an area of about 1,020 km 2 in monsoon and 704 km 2 in summer (Gupta et al. 2008). The large catchment basin (~3,500 km2) of lagoon together with high population density is the main cause of increased nutrient loading in the lagoon and poses a high risk of eutrophication. During the monsoon period, a heavy discharge of freshwater through the rivers and land runoff from the catchment basin is poured into the Chilika lagoon resulting in a marked change into the phytoplankton assemblages and physicochemical characteristics of the water. Furthermore, the spatial and temporal gradients due to tidal mixing of freshwater and seawater in the Chilika lagoon make it an ideal tropical monsoon-influenced estuarine ecosystem to examine the phytoplankton distribution and composition in relation to environmental variables.
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Fig. 1 Map of Chilika lagoon showing sampling stations. Physical boundaries delineating four sectors of the lagoon are hypothetical. NS northern sector, CS central sector, SS southern sector, OC outer channel. T1, T2, and T3 are the tide gauge stations
Given the ecological importance of phytoplankton, studies have investigated phytoplankton communities in the Chilika lagoon (Raman et al. 1990; Adhikary and Sahu 1992; Rath and Adhikary 2008; Panigrahi et al. 2009; Mohanty and Adhikary 2013). However, all these studies had limited sampling efforts in the sense that samples were collected only once in a particular season (i.e., total three times in a year). Importantly, in September 2000, an artificial inlet was dredged opened in the Chilika lagoon to restore its declining salinity and biodiversity. This hydrologic intervention had a dramatic effect on the salinity regime, tidal flux, and biodiversity including on the phytoplankton communities of lagoon (Panigrahi et al. 2009; Sahu et al. 2014). A survey conducted between 2000 and 2001 on the phytoplankton communities using 10–20-μm size plankton net reported 84 species belonging to Cyanophyta, Chlorophyta, Bacillariophyta, Dinophyta, and Rhodophyta (Rath and Adhikary 2008), while another survey undertaken for the period 2001–2003 used a gravity sedimentation method for phytoplankton collection and reported 128 species, mostly represented by
Bacillariophyta and Dinophyta (Panigrahi et al. 2009). However, the identity of only 64 dominant species was included in their publication. Interestingly, a recent study on Chilika between 2011 and 2012 recorded 81 species of algae (through 45-μm plankton net) that included both micro- and macro-algal groups (Mohanty and Adhikary 2013). From the above discussion, it is apparent that no data on the monthly variation of phytoplankton communities in Chilika lagoon is available. As it has been more than a decade since opening of an artificial inlet, it is necessary to take a detailed survey to understand the phytoplankton community composition and their environmental drivers. We hypothesized that tropical estuarine phytoplankton assemblages would exhibit pronounced seasonal and spatial distribution in response to monsoon-induced freshwater discharge and tidal influence due to the seawater. We also speculated that phytoplankton communities would be composed of a series of assemblages along the freshwater to marine salinity regime of the lagoon. The objective of this research is twofold: (i) to study the spatiotemporal dynamics and functional significance of
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phytoplankton communities in a monsoon-influenced tropical lagoonal ecosystem and (ii) to understand the role of environmental variables in controlling the community structure of phytoplankton assemblages.
Material and methods Study period and site description This study extended for 1 year (July 2011–June 2012) and has been classified into three seasons (monsoon: July–October; post-monsoon: November–February; pre-monsoon: March–June). The sampling was carried out from a network of 13 pre-selected stations covering all four sectors: (i) northern sector (NS), (ii) central sector (CS), (iii) southern sector (SS), and (iv) outer channel (OC) of the Chilika lagoon (Fig. 1). The northern sector which receives direct riverine discharge from the Mahanadi Delta has a predominantly freshwater characteristic. The central sector with intermixing of fresh and seawater is brackish, while the southern sector has comparatively higher salinity due to the seawater inflow from the Bay of Bengal through the Palur Canal. The outer channel due to large inflow of seawater from the Bay of Bengal bears typical features of a marine ecosystem. Historically, Chilika lagoon has been demarcated in these four sectors based on the salinity. Recent studies (Muduli et al. 2013) further support this demarcation based on the multidimensional scaling analysis of the physicochemical data collected from the Chilika lagoon. However, it is important to mention that this sector delineation is somewhat temporal in nature and depends on the seasonality and other cyclonic disturbances. For example, during monsoon, the whole lagoon turns into freshwater ecosystem as salinity gradient is lost. Additionally, cyclonic events accompanied with incessant precipitation such as the Phailin which happened in October 2013 also significantly alter the salinity regime of the lagoon (Sahoo et al. 2014). Water and phytoplankton sampling Surface water samples from euphotic zone (a few centimeters below the surface) were collected once every month throughout the study period (i.e., total 12 times in a year) from each of the 13 stations. Because of the large size of the lagoon and logistical considerations, diurnal and tidal variations were not accounted during
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sampling. Water temperature, pH, turbidity (nephelometric turbidity units (NTU)), and salinity were recorded in situ onboard using a handheld digital field Water Quality Checker (TOA-DKK, WQC 24). Water transparency was measured using a Secchi disc. Dissolved oxygen (DO) was measured by Winkler’s titration method (Grasshoff et al. 1999). For analysis of major dissolved nutrients [nitrate (NO3), inorganic phosphate (PO4), and silicate (SiO4)], water samples were collected in clean amber-colored HDPE bottles and transported to the laboratory on ice. Samples were filtered through Whatman GF/F (pore size 0.7 μm) filters and analyzed by the spectrophotometric procedure as described in Grasshoff et al. (1999). The absorbance was measured at 540, 880, and 810 nm, respectively, for the NO3, PO4, and SiO4, respectively, and the concentrations were expressed in micromole per liter. The precision of the NO3, PO4, and SiO4 was ±0.02, ±0.01, and ±0.02 μM, respectively (Kanuri et al. 2013). For the estimation of total chlorophyll a, 1 L of surface water was filtered through GF/F filters and extracted with 90 % acetone for 24 h at 4 °C in the dark, and the absorbance was measured in a UV–vis spectrophotometer (Thermo Scientific EvolutionTM 201) as described in Strickland and Parsons (1984). Onboard for collecting the phytoplankton, a plankton net (mesh size 20 μm, mouth diameter 0.25 m, model KC Denmark) was used to filter ~100 L of lagoon water. Samples were immediately preserved with 2 % neutral formalin–Lugol’s iodine solution. Preserved samples were finally concentrated to 80 ml by a sedimentation method (Hotzel and Croome 1999). Phytoplankton identification and enumeration Phytoplankton cells were enumerated and taxonomic identification was undertaken using a light microscope (Olympus, BX51). Phytoplankton were identified up to genus and species level using standard published keys (Desikachary 1986–89; Cox 1996; Tomas 1997; John et al. 2003). Abundance of each species was estimated by counting cells in a gridded 1-ml Sedgewick Rafter counting chamber. A subsample (1 ml) was drawn from the concentrated sample and dispensed on the counting chamber, and the counting was performed after an hour of sedimentation. The numbers of phytoplankton cells present in all 1,000 grids were calculated. Density of phytoplankton (cells L−1) was calculated using the formula (N = n × v / V), where N = total number of
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phytoplankton cells per liter of water filtered; n = number of cells in 1 ml of sample; v = volume of phytoplankton concentrate (ml); and V = volume of water (L) filtered through the plankton net.
correlations were computed using SPSS 17.0 to find the correlation between environmental parameters and phytoplankton communities.
Statistical analysis
Results and discussion
A combination of canonical correspondence analysis (CCA), non-metric multidimensional scaling (NMDS), and Pearson correlation was applied to compare the phytoplankton communities across different stations and to identify major drivers of the community composition. CCA is designed to extract synthetic environmental gradients from the ecological datasets (Braak 1988) and is based on unimodal function of the species abundance (Braak and Verdonschot 1995). CCA was mainly used to examine the environmental variables that were responsible for variation in phytoplankton community. Sampling months, sampling sectors, and stations were considered as nominal explanatory variables, and these were treated as a series of dummy variables in the data matrix. Significant environmental variables were selected by forward selection with the program CANOCO for Windows (version 4.5). The statistical significance of the axes and selected environmental variables were assessed using a Monte Carlo permutation test (499 permutations at a significance level of 0.01), which examines the statistical significance of the effect of each variable. In the diagrams, the classes of nominal explanatory variables are indicated by each centroid. Mean differences between variables were determined using one-way ANOVA (Welch F test), followed by Mann–Whitney pairwise tests when the main effect or interaction was significant at p 5 mg L−1) throughout the survey period due to its larger size, high primary productivity, and also due to churning actions resulting from strong winds. We did not find correlation between DO and phytoplankton abundance indicating the role of other possible sources (macrophytes, riverine freshwater) in contributing DO in water. In our survey, central sector of the lagoon showed considerable variation in the DO level in different seasons which could be due to various biological processes (respiration or photosynthesis). In this study, average DO values (6.8±0.2 mg L−1) were similar between
Generally, salinity in an estuary tends to decline in the monsoon season due to large freshwater inflow from rivers. Chilika lagoon was no exception to this and showed typical salinity characteristics of monsooninfluenced estuarine ecosystem. The salinity of the lagoon was minimum (9±1.2) during the southwest monsoon season primarily due to the influx of huge quantity (6,912 million cubic meters) of freshwater into the lagoon from Mahanadi Delta and Western catchment rivers (Table 1 and Fig. 1). However, as the season progressed towards post-monsoon, the influx of seawater and with concurrent increase in water evaporation increased the salinity of the lagoon to 10±1.0 which further increased to 20±1.4 during pre-monsoon season. Many tropical estuaries from India and other parts of the world exhibit similar fluctuations in salinity due to seasonal shifts in hydrology. For example, in a study from Cochin backwaters of southwest coast of India, salinity decreased to 0 during monsoon but reached to 30 during the pre-monsoon
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season (Martin et al. 2008). Similar observations have been made in other tropical ecosystems such as in the Bach Dang estuary (Vietnam) where heavy freshwater discharge during the monsoon season decreased the salinity of some stations as low as 0.1 (RochelleNewall et al. 2011). Salinity further exhibited a sector-specific variation throughout the Chilika lagoon. Northern sector during monsoon period displayed lower salinity (mean 1.1) as 78 % of freshwater inflow into the Chilika lagoon is through the northeast rivers (Muduli et al. 2013). The influence of freshwater inflow and tidal mixing with seawater generated a typical salinity gradient in the lagoon. For example, the southern sector stations (SS1, SS2, SS3) which have least tidal influence and low intrusion of freshwater displayed higher salinity (12.5) than the central sector stations (CS1, CS2, CS3, CS4) during the monsoon season (8). The influence of large inflow of freshwater was visible across stations which were separated by long distance within the lagoon. For instance, though the outer channel stations (OC1, OC2, OC3) were located considerably far from the northern sector, they displayed lower salinity (13.4) during monsoon compared to pre-monsoon (31.1) season. Historically, Chilika lagoon has experienced a wide range of salinity variation over the years. Earlier studies reported salinity value ranging from 1.4 to 6.3 in 1995 indicating that lagoon was turning towards a freshwater ecosystem (Ghosh et al. 2006). To prevent this, opening of an artificial inlet was carried out in year 2000 which had a dramatic effect on the salinity of the lagoon. Average salinity of the lagoon during our study period was 13 with values ranging from 0 (NS1, NS2 in monsoon) to 33.5 (CS4 in pre-monsoon). In year 2001– 2003, the average salinity of the lagoon was 21.5 with values ranging from 0.5 to 31.6 (Panigrahi et al. 2009). During 2009–2010, salinity ranged from 0.1 to 36 with average of 12.1 (Muduli et al. 2013). Thus, it is evident that the average salinity of the lagoon declined compared to year 2001–2003, but afterwards, salinity regime is maintained with almost no or little changes. pH The pH is one of the important parameters that regulate carbon and nutrient availability in aquatic ecosystem and thus has an effect on phytoplankton growth. Compared to seawater, pH of the coastal water varies to a greater extent. Generally, variation in pH values
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during different seasons is due to factors like assimilation of CO2 by phytoplankton and macrophytes, tidal mixing and net dilution of seawater by freshwater, low primary productivity, and decomposition of organic matter. In estuarine ecosystem due to the buffering capacity of the seawater, pH ranges from 7.8 to 8.3 (Millero 1986). Studies have also shown that phytoplankton community structure is highly correlated with pH, and differences as low as 0.1 pH unit could have an effect on species composition (Dixit et al. 1992). The pH of the Chilika lagoon remained alkaline (7.4–10.3) throughout our survey and did not vary much across sectors, but temporal variation was observed. For instance, it varied between 8.4±0.04 (monsoon) and 8.8± 0.06 (post-monsoon) in the lagoon (Table 1). In several stations particularly within the central sector, pH values peaked to 10.3 during post-monsoon season which might be due to high biological activity and/or seawater intrusion. Recent studies conducted on the water quality of Chilika lagoon have also recorded pH ranging between 6.7 and 9.98 (Muduli et al. 2012). The alkaline pH of the lagoon is particularly conducive for proliferation of seagrass beds and survival of aquatic organisms such as fishes in the Chilika lagoon. Turbidity During year 2011, high rainfall (300–197 mm; source: Odisha Rainfall Monitoring System) was recorded between July and September. Freshwater influx through the riverine system brought a high amount (369,307 Metric Ton) of suspended solids into the Chilika lagoon. The load of suspended solids present in the water is a key factor which controls the light penetration in Chilika lagoon (Panigrahi et al. 2009). High solid load thus increased turbidity and reduced the amount of sunlight that would penetrate into the water column. Turbidity along with nutrients affects the primary productivity of the lagoon through changes in phytoplankton density and distribution (Justic et al. 2005). Turbidity of the Chilika lagoon showed marked spatial and temporal variation throughout the study period depending on the tidal mixing, wind-driven circulation, and inflow of freshwater along with suspended particulate matter. Maximum turbidity (62.7 ± 11.9 NTU) was observed in pre-monsoon compared to 58.5 ±9.8 NTU in monsoon and 47.1±5.2 NTU in the postmonsoon season (Table 1). Higher turbidity in pre-monsoon season was primarily because of the strong churning of
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water current due to the action of strong southerly winds, while in monsoon season, the high turbidity could be attributed to large sediment flux into the lagoon from the riverine discharge. In addition to these seasonal factors, mechanical operations such as dredging and fishing boats which are very common in Chilika lagoon also cause bottom sediment resuspension in water column which increases the turbidity. Nutrient With regard to the trophic status, Chilika lagoon showed a wide range of concentration of dissolved nutrients (NO3, PO4, and SiO4) during the study. The source of these nutrients in lagoon could be allochthonous as well as autochthonous. In Chilika lagoon, a study conducted during year 2009–2010 has analyzed nutrient fluxes and net ecosystem production with respect to retention time of the lagoon in both high and low flow period (Muduli et al. 2013). It was observed that residence time of the water in lagoon was higher during low-flow period (summer) than the high-flow period (monsoon). In context to nutrients and production in tropical lagoons, a high flushing rate limits the accumulation of nutrient and phytoplankton standing crop. In general, northern sector which directly receives the freshwater discharge from the Mahanadi River distributaries (Daya, Bhargavi, and Nuna Rivers) displayed higher amount of nutrients compared to other three sectors (Table 1). These findings were in agreement with earlier report which measured nutrient variability with respect to phytoplankton biomass in Chilika lagoon (Panigrahi et al. 2009). The runoff water from the catchment along with monsoonal riverine influx mostly contributes to nutrient loading in the Chilika lagoon. Nitrogenous nutrients are important in lagoon ecosystem as they are taken rapidly by aquatic photosynthetic organisms and are one of the major factors regulating primary production in coastal ecosystem (Herbert 1999). Besides that, oxidized form of nitrogen such as NO3 is one of the most important indicators of water quality as excess NO3 can cause eutrophication of the water bodies. Average NO3 concentrations in Chilika lagoon were almost similar between monsoon (3.9 ± 0.28 μmol L −1 ) and postmonsoon (4.1±0.31 μmol L−1) but differed significantly with pre-monsoon (1.4 ± 0.20 μmol L −1 ) season (Table 1). Phosphate is generally considered a limiting factor for phytoplankton growth in coastal ecosystem
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(Satpathy et al. 2010). In estuarine and coastal water bodies, seawater is considered as the major source of phosphate unless there is freshwater inflow containing either domestic sewage or agro-industrial runoff (Liu et al. 2009). An earlier study from Chilika lagoon recorded an increase in phosphate concentration after opening of the new mouth suggesting that seawater influx could be the potential source of phosphate in the lagoon (Panigrahi et al. 2009). In our study, maximum PO4 concentration 1.7±0.14 μmol L−1 was recorded in post-monsoon when the freshwater flow was minimum or almost stopped suggesting that phosphate was mainly supplied in the lagoon from seawater. The silicate concentration was also noticed higher during the monsoon season. The origin of this silicate could be due to heavy inflow of freshwater from riverine distributaries and land drainage of catchment area which can carry silicate leached out from the rocks. Additionally in Chilika, silicate from the bottom sediment could also be leached out in overlying water column due to turbulence created by mechanized boats and disturbance of sediment through the dredging operations. Phytoplankton density and biomass The population density of phytoplankton exhibited very distinct spatial and temporal differences across sampling stations. In this study, highest average phytoplankton density in the lagoon was recorded in monsoon (2,385± 1,159 cells L−1) followed by pre-monsoon (1,574±250 cells L−1) and post-monsoon (1,391±330 cells L−1) (Table 1). This was in contrast with earlier studies which have observed maximum phytoplankton density in premonsoon and post-monsoon seasons, while minimum density was recorded in the monsoon (Adhikary and Sahu 1992). These differences related to maximum and minimum seasonal abundances could be attributed to two specific phytoplankton samples which were collected in July 2011 from stations CS2 and CS4. These samples contributed significantly in the overall phytoplankton cell density during monsoon as they contained very high cell abundance represented by 43,512 and 31,979 cells L−1, respectively. Taxonomic analysis of these two water samples showed overwhelming dominance of Pleurosigma normanii, a pennate member of Bacillariophyta accounting up to 98 % of total abundance in CS2 and 97 % in CS4 stations. The sharp variations in phytoplankton abundance are difficult to predict as variation is caused by complex
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interaction between several biotic and abiotic factors. Among the biotic factors in shallow ecosystem, on one side, submerged aquatic macrophytes can promote benthic algae, but on another side, they can control phytoplankton community composition by regulating nutrients and through biochemical mechanism such as allelopathy (Mulderij et al. 2007). Northern sector due to its freshwater regime and high nutrient level supports a luxurious growth of submerged macrophytes such as Potamogeton, Chara, and Hydrilla throughout the year. Station NS1 which is located in northern sector contained only 12 cells L−1 in July 2011. It is possible that allelopathy might exist in stations such as NS1, which resulted in very low phytoplankton density. However, finding experimental evidence for complex biochemical interactions under lagoonal condition warrants further investigations in future studies. Phytoplankton biomass was estimated through measurement of total Chl-a from each station on a monthly basis. Analysis of the average seasonal data of biomass suggested that it was almost similar in pre-monsoon (23.3±2.4 μg L−1) and monsoon (22.0±2.4 μg L−1) but varied with post-monsoon (10.1±0.95 μg L−1) period (Table 1). Overall, phytoplankton biomass of the lagoon differed during each sampling month (Supp. Fig. 1); however, a correlation between density and biomass was not found which is not surprising considering the high diversity of phytoplankton species and variability in chlorophyll molecules per cell with respect to changing light regime. Phytoplankton community composition The phytoplankton community in the Chilika lagoon was found to be composed of six major groups, namely Bacillariophyta (54 genera; 138 species), Dinophyta (12 genera, 38 species), Chlorophyta (25 genera, 32 species), Cyanophyta (17 genera; 29 species), Euglenophyta (6 genera; 18 species), and Chrysophyta (3 genera; 4 species) (Supp. Table 1). The dominance of Bacillariophyta over other groups is similar to observations from many other tropical estuarine environments such as Philippine mangrove estuary (Canini et al. 2013) and Na Thap Estuary of Thailand (Lueangthuwapranit et al. 2011). In total, 259 species representing freshwater, brackish, and marine phytoplankton forms were documented from Chilika lagoon. These findings highlight the importance of undertaking extensive monthly survey along spatial and temporal scales to obtain a
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greater understanding of the phytoplankton species diversity and their distribution. Earlier studies due to their limited seasonal sampling (i.e., three times in a year) could record only 97 (Raman et al. 1990), 84 (Rath and Adhikary 2008), and 128 (Panigrahi et al. 2009) phytoplankton species from the Chilika lagoon. Thus, outcome of such studies may be biased by seasonal variations in the phytoplankton community structure and may therefore underestimate the total phytoplankton diversity. The high diversity obtained in our study was due to intense monthly sampling along with filtration of large amount of water (100 L/sample) through the 20-μm plankton net. Spatiotemporal distribution of phytoplankton communities Phytoplankton communities showed marked spatial and temporal variation with respect to seasons and sectors in the Chilika lagoon (Fig. 2). Bacillariophyta were more abundant in the monsoon season with 1,879 cells L−1 which subsequently decreased to 710 cells L−1 in postmonsoon season and again increased to 1,134 cells L−1 in pre-monsoon season (Fig. 2a). When phytoplankton community composition was analyzed with respect to four ecological sectors of the lagoon, variation in their composition was clearly evident at the spatial scale. Bacillariophyta were the most abundant phytoplankton across stations located in outer channel, central, and southern sectors of the lagoon (Fig. 2b). It has been shown in previous studies that dominance of Bacillariophyta could be related to their growth rates or through their positive interaction with environmental gradients (e.g., Chan and Hamilton 2001). In this study, Bacillariophyta were dominant over other groups and constituted 57.3 % of the total cell density. The ability of Bacillariophyta to adapt rapidly to changing environmental conditions and adjust their community composition with respect to physical, chemical, and biological conditions is responsible to place them as the most important primary producer in estuarine ecosystem (Gowda et al. 2001). Bacillariophyta have been shown to be a major eukaryotic chromophytic phytoplankton group in estuarine systems including Chilika lagoon (Brogueira et al. 2007; Panigrahi et al. 2009; Pednekar et al. 2014). In the northern sector of the lagoon which is a freshwater zone of Chilika, phytoplankton population was mostly dominated by the Euglenophyta. Literature suggests that Euglenophyta occur preferably in nutrient-
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Fig. 2 Phytoplankton community composition of Chilika lagoon at temporal (a) and spatial scales (b). Means with the same letter are not significantly different
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rich freshwater ecosystem and serve as bio-indicator of organic pollution (Idiem’Opute 1990). For example, phytoplankton communities in the nutrient-rich freshwater zone of Na Thap River estuary, Thailand were largely represented by the Euglenophyta (Lueangthuwapranit et al. 2011). Phytoplankton species richness Our monthly survey documented 138 species of Bacillariophyta which was higher than earlier phytoplankton survey which reported only 30 species based on the seasonal sampling of Chilika lagoon (Mohanty and Adhikary 2013). Species diversity recovered within the Bacillariophyta was also observed highest compared to other classes in each monthly survey irrespective of the season (Supp. Fig. 2). In our study, Bacillariophyta consisting of both centric (62 species) and pennate (76 species) forms represented bulk of the phytoplankton assemblages which was in agreement with earlier studies from Chilika lagoon (Panigrahi et al. 2009). The dominance of pennate over the centric appears to be a common feature in many estuaries. For example, in Mandovi estuary, Goa, India, pennate dominated over centric (Pednekar et al. 2014). Pennate forms of Bacillariophyta observed in our study were mostly represented by Pleurosigma sp., P. normanii, Synedra sp., Thalassionema nitzschioides, and Surirella sp. Occurrence of large number of benthic pennate Bacillariophyta such as P. normanii and Surirella sp. in the surface water could be due to the disturbance of their benthic habitat by winds and water currents which might have resulted in resuspension of these species into the water column. Other possible reasons specific to Chilika lagoon could be the use of mechanized boat for fishing and dredging operations which disturbs the bottom sediment through resuspension in overlying water column. In Tagus estuary (Portugal), dredging operation has been shown to cause the benthic diatom displacement into the water column (Cabrita 2014). The centric forms of Bacillariophyta in Chilika lagoon were largely represented by Chaetoceros sp., Coscinodiscus sp., Lithodesmium undulatum, Hemiaulas sinensis, and Paralia sulcata. Of these, L. undulatum and H. sinensis have not been documented earlier from the Chilika lagoon. We also detected very low abundance of some dinophyte taxa, namely Gymnodinium (1–151 cells L−1), Alexandrium (1 cell
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L−1), and Gonyaulax (1–18 cells L−1), that are recognized globally as harmful algal bloom-forming genera (Hallegraeff et al. 1995). Furthermore, the presence and absence of these taxa also varied along seasonal scales in the lagoon. The combined number of phytoplankton species detected in each month from 13 monitoring stations varied from 32 to 102 species. Species richness was recorded maximum (mean 183 species) in pre-monsoon season and lowest (92 species) in the monsoon season indicating substantial temporal variation in phytoplankton species richness along seasonal scales. Besides species richness, the spatiotemporal dynamics of phytoplankton species varied with respect to the season and sectors in the Chilika lagoon (Table 2). These results indicate that species composition of phytoplankton assemblages progressively changed from freshwater to a marinedominated community across four sectors in continuum with salinity gradient. During our 12-month survey period, the most consistent and abundant taxa encountered in the lagoon were P. normanii (5 to 4,821 cells L−1) and Dictyocha sp. (1–716 cells L−1). Of these, Dictyocha is known as bloom-forming species which at higher cell densities can stimulate excess mucus production in fish gills and may lead to fish deaths (UNESCO 2001). Phytoplankton composition and environmental gradients Phytoplankton communities in a lagoon are mostly determined by fluxes of nutrients and environmental factors which in turn depend on the hydrological cycles. It should be noted that finding a single parameter which could explain the entire variability in community composition is very unlikely in most of the environmental surveys. This is due to the fact that under field conditions, multiple environmental factors interact together to influence community diversity and distribution. The CCA ordination of phytoplankton species in relation to the environmental variables suggested that community responded to both spatial and seasonal variations (Fig. 3). CCA identified the relationships among phytoplankton abundance, composition, and physicochemical parameters. The overall proportion of variance explained by the three principal CCA axes was 86.4 % (Table 3). The first axis was mainly determined by the influence of seawater gradient, which could explain 44.8 % of the total variance in species–environment
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Table 2 Spatial and temporal variations in some dominant species of phytoplankton recovered from Chilika lagoon Season
Phytoplankton taxa
Southern sector Monsoon
Dictyocha sp.a (48), Thalassiothrix longissimaa (12)
Postmonsoon Pre-monsoon
Pleurosigma normaniia (47), Pleurosigma sp. (11) Dictyocha sp.a (45), Synedra sp.abc (25)
Central sector Monsoon
Pleurosigma normaniia (88), Dictyocha sp.a (2.6)
Postmonsoon Pre-monsoon
Anabaena sp.b (21), Pleurosigma sp. (16) Prorocentrum minimuma (16), Synedra sp.abc (10)
Northern sector Monsoon
Anabaena sp. b (23.9), Eudorina sp.b (16.8)
Postmonsoon Pre-monsoon
Trachelomonas sp.b (69.5), Oscillatoria sp.b (4.4) Cylindrospermum sp.b (40.8), Aphanocapsa sp.b (4.5)
Outer channel Monsoon
Nitzschia sp.abc (30), Pleurosigma sp. (12)
Postmonsoon Pre-monsoon
Chaetoceros sp.a (28), Surirella sp.abc (17) Thalassiosira subtilisa (20), Pseudonitzschia pungensa (10)
Number in the parenthesis of each species denotes percentage abundance of that particular species. The preferred salinity regime (marine, freshwater, brackish) for species based on the available literature is also included. Many of the major species, for example Thalassiothrix longissima, Pleurosigma normanii, Pleurosigma sp. Anabaena sp., Eudorina sp. Trachelomonas sp., Oscillatoria sp., Nitzschia sp., Chaetoceros sp., and Pseudonitzschia pungens, are cosmopolitan in their distribution, while other species such as Prorocentrum minimum and Thalassiosira subtilis are restricted to tropical and temperate regions a
Marine
b
Freshwater
c
Brackish
relationship (r=0.80). Salinity (r=−0.65) and pH (r= 0.39) were found to be strong contributors to the first CCA axis. The second axis explained 23.5 % of the variance in the species–environment relationship (r= 0.68) and was mainly determined by light availability. Transparency (r=0.31) and turbidity (r=−0.29) were the strongest contributors to the second CCA axis. The third axis explained 18.1 % of the variance in the species– environment relationship (r=0.60), and silica contents (r=0.31) were the strongest contributors to the third CCA axis.
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In Chilika lagoon, northern sector where river discharge occurs had low salinity and high DO and silica. Euglenophyta, Chlorophyta, and Cyanophyta were more abundant in northern sector (Fig. 3a). Southern sector being brackish in salinity and having water of high transparency was mostly represented by Chrysophyta and Dinophyta. Outer channel had the highest salinity and turbidity level. Bacillariophyta showed higher abundance in outer channel and central sector, where salinity levels were comparatively higher than the other sectors of the lagoon. Among central sector stations, CS3 showed more similarity with stations from the northern sector. This denoted that CS3 was more influenced by river discharge than seawater intrusion based on its closer proximity to the northern sector. Seasonal data analysis based on CCA showed that monsoon had the largest variation in species abundance and environmental variables (Fig. 3b). A strong positive correlation was observed between phytoplankton density and salinity during pre-monsoon (r=0.382, p
Spatiotemporal distribution and composition of phytoplankton assemblages in a coastal tropical lagoon: Chilika, India Suchismita Srichandan & Ji Yoon Kim & Punyasloke Bhadury & Saroja K. Barik & Pradipta R. Muduli & Rabindro N. Samal & Ajit K. Pattnaik & Gurdeep Rastogi Received: 31 July 2014 / Accepted: 1 December 2014 # Springer International Publishing Switzerland 2015
Abstract The Asia’s largest lagoon, Chilika, is a shallow water estuary and a designated “Ramsar” site located in the east coast of India. The spatiotemporal diversity of phytoplankton based on the monthly sampling between July 2011 and June 2012 was investigated in relation to physicochemical variables of the surface water column from 13 stations. The salinity was minimum (average 9) during the monsoon which was primarily due to riverine discharge. As the season progressed towards post-monsoon, average salinity of the whole lagoon reached to 10 which further increased to 20 during pre-monsoon season. A total of 259 species of phytoplankton, mostly dominated by the
Electronic supplementary material The online version of this article (doi:10.1007/s10661-014-4212-9) contains supplementary material, which is available to authorized users.
Bacillariophyta (138 species) followed by Dinophyta (38 species), Chlorophyta (32 species), Cyanophyta (29 species), Euglenophyta (18 species), and Chrysophyta (4 species), were recorded in this study. Different ecological sectors of the lagoon (except the northern sector) were dominated by diatoms, while the northern sector due to its freshwater regime supported large population of euglenoids. Based on the multivariate ordination analysis, salinity regime and light availability played important role in determining the distribution, diversity, and composition of phytoplankton communities. Overall, this study documented a very high diversity of phytoplankton and highlighted the importance of taking extensive sampling in getting a clearer understanding of phytoplankton community structure in less-studied environments such as Chilika lagoon.
S. Srichandan : S. K. Barik : P. R. Muduli : R. N. Samal : A. K. Pattnaik : G. Rastogi (*) Wetland Research and Training Centre, Chilika Development Authority, Barkul, Balugaon, Odisha 752030, India e-mail: [email protected]
Keywords Phytoplankton . Monsoon . Salinity . Spatiotemporal . Estuary
J. Y. Kim Department of Integrated Biological Science, Pusan National University, Pusan, South Korea
Coastal lagoons are highly productive ecosystems providing a range of ecological services related to the supply of food and fodder, protection from floods, groundwater recharge, and sequestration of contaminants. These ecosystems are under intense anthropogenic pressure as they receive pollutants and nutrients from the surrounding watershed community and are liable to become eutrophic (McGlathery et al. 2007; Dube and
P. Bhadury Integrative Taxonomy and Microbial Ecology Research Group, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, West Bengal 741246, India
Introduction
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Jayaraman 2008). Due to the simultaneous connectivity with rivers and sea, coastal lagoons represent a transition zone where freshwater and marine ecosystems are linked to each other. The mixing of nutrient-rich turbid river discharge with the nutrient-poor marine water generates a continuous gradient of salinity, nutrient, and other environmental gradients which has a strong impact on the spatial and temporal distribution of phytoplankton communities. Phytoplankton being the primary producers in the lagoon ecosystem have a crucial role in the nutrient cycling as well as balancing the overall food web dynamics (e.g., Dannielsdottir et al. 2007). In addition to ensuring ecological services, phytoplankton species composition is considered an efficient bio-indicator of water quality as their distribution strongly correlates with various physical, chemical, biological, and hydrological factors as well as interactions among them (Paerl et al. 2010). These complex environmental gradients also show dynamic seasonal variation. Thus, study of spatial and temporal changes in phytoplankton communities with respect to the environmental variables is important to assess the water quality and getting a clearer understanding of net ecosystem production in the lagoon. Considering the ecological significance of phytoplankton, numerous studies have targeted phytoplankton communities in the freshwater (e.g., Stomp et al. 2011; Tian et al. 2013), marine (e.g., Cermeno et al. 2013; Edwards et al. 2013), and estuarine ecosystems (e.g., Brogueira et al. 2007; Paerl et al. 2010). These studies have provided several interesting mechanistic insights on the community assemblage, functional traits, and the seasonal dynamics of phytoplankton communities in relation to environmental gradients. Stomp et al. (2011) examined the freshwater phytoplankton diversity in 540 lagoons and observed that local environmental factors were the major drivers of phytoplankton species composition. For instance, water color, phosphorous, and alkalinity were the major environmental factors for controlling phytoplankton species composition in European lakes (Maileht et al. 2013), while ammonium and phosphorus played an important role in case of freshwater lake ecosystems from China (Tian et al. 2013). Estuarine and coastal tropical ecosystems are more challenging when it comes to determining environmental drivers of phytoplankton community. This is due to their highly dynamic nature with respect to the
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hydrology, nutrient cycling, and biotic factors. Different studies suggest that multiple environmental factors along with the site-specific factors best correlate with variation in phytoplankton communities in many tropical estuaries. For instance, salinity and turbidity were the principal factors which explained the seasonal and geographical variation in Chlorophyta, Euglenophyta, and Cyanophyta in a tropical inland freshwater estuary of southern Thailand (Lueangthuwapranit et al. 2011). Site-specific factors, e.g., heavy metals, together with salinity played an important role in structuring phytoplankton composition in a tropical coastal estuary of Vietnam (RochelleNewall et al. 2011). While other factors such as temperature, silicate, and phosphorus along with salinity controlled the phytoplankton species composition and distribution in Tagus estuary, Portugal (Brogueira et al. 2007). The Chilika is the largest brackish water lagoon in Asia located in the Odisha state along the east coast of India (19° 28′–19° 54′ N and 85° 06′–85° 35′ E) (Fig. 1). The lagoon is well known for socioeconomics, biodiversity, ecological services, and is a designated “Ramsar site-wetland of international importance.” The detailed description of this ideal lagoon ecosystem in relation to hydrology, geomorphology, and biodiversity is described elsewhere (Sahu et al. 2014). The shallow depth of lagoon (average ~2 m) allows sunlight to penetrate mostly to the bottom, supporting a high diversity of planktonic communities, benthic organisms, and aquatic macrophytes. Freshwater inflow is mostly from the 12 major rivers which together forms the catchment basin of the lagoon. The lagoon covers an area of about 1,020 km 2 in monsoon and 704 km 2 in summer (Gupta et al. 2008). The large catchment basin (~3,500 km2) of lagoon together with high population density is the main cause of increased nutrient loading in the lagoon and poses a high risk of eutrophication. During the monsoon period, a heavy discharge of freshwater through the rivers and land runoff from the catchment basin is poured into the Chilika lagoon resulting in a marked change into the phytoplankton assemblages and physicochemical characteristics of the water. Furthermore, the spatial and temporal gradients due to tidal mixing of freshwater and seawater in the Chilika lagoon make it an ideal tropical monsoon-influenced estuarine ecosystem to examine the phytoplankton distribution and composition in relation to environmental variables.
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Fig. 1 Map of Chilika lagoon showing sampling stations. Physical boundaries delineating four sectors of the lagoon are hypothetical. NS northern sector, CS central sector, SS southern sector, OC outer channel. T1, T2, and T3 are the tide gauge stations
Given the ecological importance of phytoplankton, studies have investigated phytoplankton communities in the Chilika lagoon (Raman et al. 1990; Adhikary and Sahu 1992; Rath and Adhikary 2008; Panigrahi et al. 2009; Mohanty and Adhikary 2013). However, all these studies had limited sampling efforts in the sense that samples were collected only once in a particular season (i.e., total three times in a year). Importantly, in September 2000, an artificial inlet was dredged opened in the Chilika lagoon to restore its declining salinity and biodiversity. This hydrologic intervention had a dramatic effect on the salinity regime, tidal flux, and biodiversity including on the phytoplankton communities of lagoon (Panigrahi et al. 2009; Sahu et al. 2014). A survey conducted between 2000 and 2001 on the phytoplankton communities using 10–20-μm size plankton net reported 84 species belonging to Cyanophyta, Chlorophyta, Bacillariophyta, Dinophyta, and Rhodophyta (Rath and Adhikary 2008), while another survey undertaken for the period 2001–2003 used a gravity sedimentation method for phytoplankton collection and reported 128 species, mostly represented by
Bacillariophyta and Dinophyta (Panigrahi et al. 2009). However, the identity of only 64 dominant species was included in their publication. Interestingly, a recent study on Chilika between 2011 and 2012 recorded 81 species of algae (through 45-μm plankton net) that included both micro- and macro-algal groups (Mohanty and Adhikary 2013). From the above discussion, it is apparent that no data on the monthly variation of phytoplankton communities in Chilika lagoon is available. As it has been more than a decade since opening of an artificial inlet, it is necessary to take a detailed survey to understand the phytoplankton community composition and their environmental drivers. We hypothesized that tropical estuarine phytoplankton assemblages would exhibit pronounced seasonal and spatial distribution in response to monsoon-induced freshwater discharge and tidal influence due to the seawater. We also speculated that phytoplankton communities would be composed of a series of assemblages along the freshwater to marine salinity regime of the lagoon. The objective of this research is twofold: (i) to study the spatiotemporal dynamics and functional significance of
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phytoplankton communities in a monsoon-influenced tropical lagoonal ecosystem and (ii) to understand the role of environmental variables in controlling the community structure of phytoplankton assemblages.
Material and methods Study period and site description This study extended for 1 year (July 2011–June 2012) and has been classified into three seasons (monsoon: July–October; post-monsoon: November–February; pre-monsoon: March–June). The sampling was carried out from a network of 13 pre-selected stations covering all four sectors: (i) northern sector (NS), (ii) central sector (CS), (iii) southern sector (SS), and (iv) outer channel (OC) of the Chilika lagoon (Fig. 1). The northern sector which receives direct riverine discharge from the Mahanadi Delta has a predominantly freshwater characteristic. The central sector with intermixing of fresh and seawater is brackish, while the southern sector has comparatively higher salinity due to the seawater inflow from the Bay of Bengal through the Palur Canal. The outer channel due to large inflow of seawater from the Bay of Bengal bears typical features of a marine ecosystem. Historically, Chilika lagoon has been demarcated in these four sectors based on the salinity. Recent studies (Muduli et al. 2013) further support this demarcation based on the multidimensional scaling analysis of the physicochemical data collected from the Chilika lagoon. However, it is important to mention that this sector delineation is somewhat temporal in nature and depends on the seasonality and other cyclonic disturbances. For example, during monsoon, the whole lagoon turns into freshwater ecosystem as salinity gradient is lost. Additionally, cyclonic events accompanied with incessant precipitation such as the Phailin which happened in October 2013 also significantly alter the salinity regime of the lagoon (Sahoo et al. 2014). Water and phytoplankton sampling Surface water samples from euphotic zone (a few centimeters below the surface) were collected once every month throughout the study period (i.e., total 12 times in a year) from each of the 13 stations. Because of the large size of the lagoon and logistical considerations, diurnal and tidal variations were not accounted during
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sampling. Water temperature, pH, turbidity (nephelometric turbidity units (NTU)), and salinity were recorded in situ onboard using a handheld digital field Water Quality Checker (TOA-DKK, WQC 24). Water transparency was measured using a Secchi disc. Dissolved oxygen (DO) was measured by Winkler’s titration method (Grasshoff et al. 1999). For analysis of major dissolved nutrients [nitrate (NO3), inorganic phosphate (PO4), and silicate (SiO4)], water samples were collected in clean amber-colored HDPE bottles and transported to the laboratory on ice. Samples were filtered through Whatman GF/F (pore size 0.7 μm) filters and analyzed by the spectrophotometric procedure as described in Grasshoff et al. (1999). The absorbance was measured at 540, 880, and 810 nm, respectively, for the NO3, PO4, and SiO4, respectively, and the concentrations were expressed in micromole per liter. The precision of the NO3, PO4, and SiO4 was ±0.02, ±0.01, and ±0.02 μM, respectively (Kanuri et al. 2013). For the estimation of total chlorophyll a, 1 L of surface water was filtered through GF/F filters and extracted with 90 % acetone for 24 h at 4 °C in the dark, and the absorbance was measured in a UV–vis spectrophotometer (Thermo Scientific EvolutionTM 201) as described in Strickland and Parsons (1984). Onboard for collecting the phytoplankton, a plankton net (mesh size 20 μm, mouth diameter 0.25 m, model KC Denmark) was used to filter ~100 L of lagoon water. Samples were immediately preserved with 2 % neutral formalin–Lugol’s iodine solution. Preserved samples were finally concentrated to 80 ml by a sedimentation method (Hotzel and Croome 1999). Phytoplankton identification and enumeration Phytoplankton cells were enumerated and taxonomic identification was undertaken using a light microscope (Olympus, BX51). Phytoplankton were identified up to genus and species level using standard published keys (Desikachary 1986–89; Cox 1996; Tomas 1997; John et al. 2003). Abundance of each species was estimated by counting cells in a gridded 1-ml Sedgewick Rafter counting chamber. A subsample (1 ml) was drawn from the concentrated sample and dispensed on the counting chamber, and the counting was performed after an hour of sedimentation. The numbers of phytoplankton cells present in all 1,000 grids were calculated. Density of phytoplankton (cells L−1) was calculated using the formula (N = n × v / V), where N = total number of
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phytoplankton cells per liter of water filtered; n = number of cells in 1 ml of sample; v = volume of phytoplankton concentrate (ml); and V = volume of water (L) filtered through the plankton net.
correlations were computed using SPSS 17.0 to find the correlation between environmental parameters and phytoplankton communities.
Statistical analysis
Results and discussion
A combination of canonical correspondence analysis (CCA), non-metric multidimensional scaling (NMDS), and Pearson correlation was applied to compare the phytoplankton communities across different stations and to identify major drivers of the community composition. CCA is designed to extract synthetic environmental gradients from the ecological datasets (Braak 1988) and is based on unimodal function of the species abundance (Braak and Verdonschot 1995). CCA was mainly used to examine the environmental variables that were responsible for variation in phytoplankton community. Sampling months, sampling sectors, and stations were considered as nominal explanatory variables, and these were treated as a series of dummy variables in the data matrix. Significant environmental variables were selected by forward selection with the program CANOCO for Windows (version 4.5). The statistical significance of the axes and selected environmental variables were assessed using a Monte Carlo permutation test (499 permutations at a significance level of 0.01), which examines the statistical significance of the effect of each variable. In the diagrams, the classes of nominal explanatory variables are indicated by each centroid. Mean differences between variables were determined using one-way ANOVA (Welch F test), followed by Mann–Whitney pairwise tests when the main effect or interaction was significant at p 5 mg L−1) throughout the survey period due to its larger size, high primary productivity, and also due to churning actions resulting from strong winds. We did not find correlation between DO and phytoplankton abundance indicating the role of other possible sources (macrophytes, riverine freshwater) in contributing DO in water. In our survey, central sector of the lagoon showed considerable variation in the DO level in different seasons which could be due to various biological processes (respiration or photosynthesis). In this study, average DO values (6.8±0.2 mg L−1) were similar between
Generally, salinity in an estuary tends to decline in the monsoon season due to large freshwater inflow from rivers. Chilika lagoon was no exception to this and showed typical salinity characteristics of monsooninfluenced estuarine ecosystem. The salinity of the lagoon was minimum (9±1.2) during the southwest monsoon season primarily due to the influx of huge quantity (6,912 million cubic meters) of freshwater into the lagoon from Mahanadi Delta and Western catchment rivers (Table 1 and Fig. 1). However, as the season progressed towards post-monsoon, the influx of seawater and with concurrent increase in water evaporation increased the salinity of the lagoon to 10±1.0 which further increased to 20±1.4 during pre-monsoon season. Many tropical estuaries from India and other parts of the world exhibit similar fluctuations in salinity due to seasonal shifts in hydrology. For example, in a study from Cochin backwaters of southwest coast of India, salinity decreased to 0 during monsoon but reached to 30 during the pre-monsoon
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season (Martin et al. 2008). Similar observations have been made in other tropical ecosystems such as in the Bach Dang estuary (Vietnam) where heavy freshwater discharge during the monsoon season decreased the salinity of some stations as low as 0.1 (RochelleNewall et al. 2011). Salinity further exhibited a sector-specific variation throughout the Chilika lagoon. Northern sector during monsoon period displayed lower salinity (mean 1.1) as 78 % of freshwater inflow into the Chilika lagoon is through the northeast rivers (Muduli et al. 2013). The influence of freshwater inflow and tidal mixing with seawater generated a typical salinity gradient in the lagoon. For example, the southern sector stations (SS1, SS2, SS3) which have least tidal influence and low intrusion of freshwater displayed higher salinity (12.5) than the central sector stations (CS1, CS2, CS3, CS4) during the monsoon season (8). The influence of large inflow of freshwater was visible across stations which were separated by long distance within the lagoon. For instance, though the outer channel stations (OC1, OC2, OC3) were located considerably far from the northern sector, they displayed lower salinity (13.4) during monsoon compared to pre-monsoon (31.1) season. Historically, Chilika lagoon has experienced a wide range of salinity variation over the years. Earlier studies reported salinity value ranging from 1.4 to 6.3 in 1995 indicating that lagoon was turning towards a freshwater ecosystem (Ghosh et al. 2006). To prevent this, opening of an artificial inlet was carried out in year 2000 which had a dramatic effect on the salinity of the lagoon. Average salinity of the lagoon during our study period was 13 with values ranging from 0 (NS1, NS2 in monsoon) to 33.5 (CS4 in pre-monsoon). In year 2001– 2003, the average salinity of the lagoon was 21.5 with values ranging from 0.5 to 31.6 (Panigrahi et al. 2009). During 2009–2010, salinity ranged from 0.1 to 36 with average of 12.1 (Muduli et al. 2013). Thus, it is evident that the average salinity of the lagoon declined compared to year 2001–2003, but afterwards, salinity regime is maintained with almost no or little changes. pH The pH is one of the important parameters that regulate carbon and nutrient availability in aquatic ecosystem and thus has an effect on phytoplankton growth. Compared to seawater, pH of the coastal water varies to a greater extent. Generally, variation in pH values
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during different seasons is due to factors like assimilation of CO2 by phytoplankton and macrophytes, tidal mixing and net dilution of seawater by freshwater, low primary productivity, and decomposition of organic matter. In estuarine ecosystem due to the buffering capacity of the seawater, pH ranges from 7.8 to 8.3 (Millero 1986). Studies have also shown that phytoplankton community structure is highly correlated with pH, and differences as low as 0.1 pH unit could have an effect on species composition (Dixit et al. 1992). The pH of the Chilika lagoon remained alkaline (7.4–10.3) throughout our survey and did not vary much across sectors, but temporal variation was observed. For instance, it varied between 8.4±0.04 (monsoon) and 8.8± 0.06 (post-monsoon) in the lagoon (Table 1). In several stations particularly within the central sector, pH values peaked to 10.3 during post-monsoon season which might be due to high biological activity and/or seawater intrusion. Recent studies conducted on the water quality of Chilika lagoon have also recorded pH ranging between 6.7 and 9.98 (Muduli et al. 2012). The alkaline pH of the lagoon is particularly conducive for proliferation of seagrass beds and survival of aquatic organisms such as fishes in the Chilika lagoon. Turbidity During year 2011, high rainfall (300–197 mm; source: Odisha Rainfall Monitoring System) was recorded between July and September. Freshwater influx through the riverine system brought a high amount (369,307 Metric Ton) of suspended solids into the Chilika lagoon. The load of suspended solids present in the water is a key factor which controls the light penetration in Chilika lagoon (Panigrahi et al. 2009). High solid load thus increased turbidity and reduced the amount of sunlight that would penetrate into the water column. Turbidity along with nutrients affects the primary productivity of the lagoon through changes in phytoplankton density and distribution (Justic et al. 2005). Turbidity of the Chilika lagoon showed marked spatial and temporal variation throughout the study period depending on the tidal mixing, wind-driven circulation, and inflow of freshwater along with suspended particulate matter. Maximum turbidity (62.7 ± 11.9 NTU) was observed in pre-monsoon compared to 58.5 ±9.8 NTU in monsoon and 47.1±5.2 NTU in the postmonsoon season (Table 1). Higher turbidity in pre-monsoon season was primarily because of the strong churning of
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water current due to the action of strong southerly winds, while in monsoon season, the high turbidity could be attributed to large sediment flux into the lagoon from the riverine discharge. In addition to these seasonal factors, mechanical operations such as dredging and fishing boats which are very common in Chilika lagoon also cause bottom sediment resuspension in water column which increases the turbidity. Nutrient With regard to the trophic status, Chilika lagoon showed a wide range of concentration of dissolved nutrients (NO3, PO4, and SiO4) during the study. The source of these nutrients in lagoon could be allochthonous as well as autochthonous. In Chilika lagoon, a study conducted during year 2009–2010 has analyzed nutrient fluxes and net ecosystem production with respect to retention time of the lagoon in both high and low flow period (Muduli et al. 2013). It was observed that residence time of the water in lagoon was higher during low-flow period (summer) than the high-flow period (monsoon). In context to nutrients and production in tropical lagoons, a high flushing rate limits the accumulation of nutrient and phytoplankton standing crop. In general, northern sector which directly receives the freshwater discharge from the Mahanadi River distributaries (Daya, Bhargavi, and Nuna Rivers) displayed higher amount of nutrients compared to other three sectors (Table 1). These findings were in agreement with earlier report which measured nutrient variability with respect to phytoplankton biomass in Chilika lagoon (Panigrahi et al. 2009). The runoff water from the catchment along with monsoonal riverine influx mostly contributes to nutrient loading in the Chilika lagoon. Nitrogenous nutrients are important in lagoon ecosystem as they are taken rapidly by aquatic photosynthetic organisms and are one of the major factors regulating primary production in coastal ecosystem (Herbert 1999). Besides that, oxidized form of nitrogen such as NO3 is one of the most important indicators of water quality as excess NO3 can cause eutrophication of the water bodies. Average NO3 concentrations in Chilika lagoon were almost similar between monsoon (3.9 ± 0.28 μmol L −1 ) and postmonsoon (4.1±0.31 μmol L−1) but differed significantly with pre-monsoon (1.4 ± 0.20 μmol L −1 ) season (Table 1). Phosphate is generally considered a limiting factor for phytoplankton growth in coastal ecosystem
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(Satpathy et al. 2010). In estuarine and coastal water bodies, seawater is considered as the major source of phosphate unless there is freshwater inflow containing either domestic sewage or agro-industrial runoff (Liu et al. 2009). An earlier study from Chilika lagoon recorded an increase in phosphate concentration after opening of the new mouth suggesting that seawater influx could be the potential source of phosphate in the lagoon (Panigrahi et al. 2009). In our study, maximum PO4 concentration 1.7±0.14 μmol L−1 was recorded in post-monsoon when the freshwater flow was minimum or almost stopped suggesting that phosphate was mainly supplied in the lagoon from seawater. The silicate concentration was also noticed higher during the monsoon season. The origin of this silicate could be due to heavy inflow of freshwater from riverine distributaries and land drainage of catchment area which can carry silicate leached out from the rocks. Additionally in Chilika, silicate from the bottom sediment could also be leached out in overlying water column due to turbulence created by mechanized boats and disturbance of sediment through the dredging operations. Phytoplankton density and biomass The population density of phytoplankton exhibited very distinct spatial and temporal differences across sampling stations. In this study, highest average phytoplankton density in the lagoon was recorded in monsoon (2,385± 1,159 cells L−1) followed by pre-monsoon (1,574±250 cells L−1) and post-monsoon (1,391±330 cells L−1) (Table 1). This was in contrast with earlier studies which have observed maximum phytoplankton density in premonsoon and post-monsoon seasons, while minimum density was recorded in the monsoon (Adhikary and Sahu 1992). These differences related to maximum and minimum seasonal abundances could be attributed to two specific phytoplankton samples which were collected in July 2011 from stations CS2 and CS4. These samples contributed significantly in the overall phytoplankton cell density during monsoon as they contained very high cell abundance represented by 43,512 and 31,979 cells L−1, respectively. Taxonomic analysis of these two water samples showed overwhelming dominance of Pleurosigma normanii, a pennate member of Bacillariophyta accounting up to 98 % of total abundance in CS2 and 97 % in CS4 stations. The sharp variations in phytoplankton abundance are difficult to predict as variation is caused by complex
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interaction between several biotic and abiotic factors. Among the biotic factors in shallow ecosystem, on one side, submerged aquatic macrophytes can promote benthic algae, but on another side, they can control phytoplankton community composition by regulating nutrients and through biochemical mechanism such as allelopathy (Mulderij et al. 2007). Northern sector due to its freshwater regime and high nutrient level supports a luxurious growth of submerged macrophytes such as Potamogeton, Chara, and Hydrilla throughout the year. Station NS1 which is located in northern sector contained only 12 cells L−1 in July 2011. It is possible that allelopathy might exist in stations such as NS1, which resulted in very low phytoplankton density. However, finding experimental evidence for complex biochemical interactions under lagoonal condition warrants further investigations in future studies. Phytoplankton biomass was estimated through measurement of total Chl-a from each station on a monthly basis. Analysis of the average seasonal data of biomass suggested that it was almost similar in pre-monsoon (23.3±2.4 μg L−1) and monsoon (22.0±2.4 μg L−1) but varied with post-monsoon (10.1±0.95 μg L−1) period (Table 1). Overall, phytoplankton biomass of the lagoon differed during each sampling month (Supp. Fig. 1); however, a correlation between density and biomass was not found which is not surprising considering the high diversity of phytoplankton species and variability in chlorophyll molecules per cell with respect to changing light regime. Phytoplankton community composition The phytoplankton community in the Chilika lagoon was found to be composed of six major groups, namely Bacillariophyta (54 genera; 138 species), Dinophyta (12 genera, 38 species), Chlorophyta (25 genera, 32 species), Cyanophyta (17 genera; 29 species), Euglenophyta (6 genera; 18 species), and Chrysophyta (3 genera; 4 species) (Supp. Table 1). The dominance of Bacillariophyta over other groups is similar to observations from many other tropical estuarine environments such as Philippine mangrove estuary (Canini et al. 2013) and Na Thap Estuary of Thailand (Lueangthuwapranit et al. 2011). In total, 259 species representing freshwater, brackish, and marine phytoplankton forms were documented from Chilika lagoon. These findings highlight the importance of undertaking extensive monthly survey along spatial and temporal scales to obtain a
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greater understanding of the phytoplankton species diversity and their distribution. Earlier studies due to their limited seasonal sampling (i.e., three times in a year) could record only 97 (Raman et al. 1990), 84 (Rath and Adhikary 2008), and 128 (Panigrahi et al. 2009) phytoplankton species from the Chilika lagoon. Thus, outcome of such studies may be biased by seasonal variations in the phytoplankton community structure and may therefore underestimate the total phytoplankton diversity. The high diversity obtained in our study was due to intense monthly sampling along with filtration of large amount of water (100 L/sample) through the 20-μm plankton net. Spatiotemporal distribution of phytoplankton communities Phytoplankton communities showed marked spatial and temporal variation with respect to seasons and sectors in the Chilika lagoon (Fig. 2). Bacillariophyta were more abundant in the monsoon season with 1,879 cells L−1 which subsequently decreased to 710 cells L−1 in postmonsoon season and again increased to 1,134 cells L−1 in pre-monsoon season (Fig. 2a). When phytoplankton community composition was analyzed with respect to four ecological sectors of the lagoon, variation in their composition was clearly evident at the spatial scale. Bacillariophyta were the most abundant phytoplankton across stations located in outer channel, central, and southern sectors of the lagoon (Fig. 2b). It has been shown in previous studies that dominance of Bacillariophyta could be related to their growth rates or through their positive interaction with environmental gradients (e.g., Chan and Hamilton 2001). In this study, Bacillariophyta were dominant over other groups and constituted 57.3 % of the total cell density. The ability of Bacillariophyta to adapt rapidly to changing environmental conditions and adjust their community composition with respect to physical, chemical, and biological conditions is responsible to place them as the most important primary producer in estuarine ecosystem (Gowda et al. 2001). Bacillariophyta have been shown to be a major eukaryotic chromophytic phytoplankton group in estuarine systems including Chilika lagoon (Brogueira et al. 2007; Panigrahi et al. 2009; Pednekar et al. 2014). In the northern sector of the lagoon which is a freshwater zone of Chilika, phytoplankton population was mostly dominated by the Euglenophyta. Literature suggests that Euglenophyta occur preferably in nutrient-
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Fig. 2 Phytoplankton community composition of Chilika lagoon at temporal (a) and spatial scales (b). Means with the same letter are not significantly different
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rich freshwater ecosystem and serve as bio-indicator of organic pollution (Idiem’Opute 1990). For example, phytoplankton communities in the nutrient-rich freshwater zone of Na Thap River estuary, Thailand were largely represented by the Euglenophyta (Lueangthuwapranit et al. 2011). Phytoplankton species richness Our monthly survey documented 138 species of Bacillariophyta which was higher than earlier phytoplankton survey which reported only 30 species based on the seasonal sampling of Chilika lagoon (Mohanty and Adhikary 2013). Species diversity recovered within the Bacillariophyta was also observed highest compared to other classes in each monthly survey irrespective of the season (Supp. Fig. 2). In our study, Bacillariophyta consisting of both centric (62 species) and pennate (76 species) forms represented bulk of the phytoplankton assemblages which was in agreement with earlier studies from Chilika lagoon (Panigrahi et al. 2009). The dominance of pennate over the centric appears to be a common feature in many estuaries. For example, in Mandovi estuary, Goa, India, pennate dominated over centric (Pednekar et al. 2014). Pennate forms of Bacillariophyta observed in our study were mostly represented by Pleurosigma sp., P. normanii, Synedra sp., Thalassionema nitzschioides, and Surirella sp. Occurrence of large number of benthic pennate Bacillariophyta such as P. normanii and Surirella sp. in the surface water could be due to the disturbance of their benthic habitat by winds and water currents which might have resulted in resuspension of these species into the water column. Other possible reasons specific to Chilika lagoon could be the use of mechanized boat for fishing and dredging operations which disturbs the bottom sediment through resuspension in overlying water column. In Tagus estuary (Portugal), dredging operation has been shown to cause the benthic diatom displacement into the water column (Cabrita 2014). The centric forms of Bacillariophyta in Chilika lagoon were largely represented by Chaetoceros sp., Coscinodiscus sp., Lithodesmium undulatum, Hemiaulas sinensis, and Paralia sulcata. Of these, L. undulatum and H. sinensis have not been documented earlier from the Chilika lagoon. We also detected very low abundance of some dinophyte taxa, namely Gymnodinium (1–151 cells L−1), Alexandrium (1 cell
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L−1), and Gonyaulax (1–18 cells L−1), that are recognized globally as harmful algal bloom-forming genera (Hallegraeff et al. 1995). Furthermore, the presence and absence of these taxa also varied along seasonal scales in the lagoon. The combined number of phytoplankton species detected in each month from 13 monitoring stations varied from 32 to 102 species. Species richness was recorded maximum (mean 183 species) in pre-monsoon season and lowest (92 species) in the monsoon season indicating substantial temporal variation in phytoplankton species richness along seasonal scales. Besides species richness, the spatiotemporal dynamics of phytoplankton species varied with respect to the season and sectors in the Chilika lagoon (Table 2). These results indicate that species composition of phytoplankton assemblages progressively changed from freshwater to a marinedominated community across four sectors in continuum with salinity gradient. During our 12-month survey period, the most consistent and abundant taxa encountered in the lagoon were P. normanii (5 to 4,821 cells L−1) and Dictyocha sp. (1–716 cells L−1). Of these, Dictyocha is known as bloom-forming species which at higher cell densities can stimulate excess mucus production in fish gills and may lead to fish deaths (UNESCO 2001). Phytoplankton composition and environmental gradients Phytoplankton communities in a lagoon are mostly determined by fluxes of nutrients and environmental factors which in turn depend on the hydrological cycles. It should be noted that finding a single parameter which could explain the entire variability in community composition is very unlikely in most of the environmental surveys. This is due to the fact that under field conditions, multiple environmental factors interact together to influence community diversity and distribution. The CCA ordination of phytoplankton species in relation to the environmental variables suggested that community responded to both spatial and seasonal variations (Fig. 3). CCA identified the relationships among phytoplankton abundance, composition, and physicochemical parameters. The overall proportion of variance explained by the three principal CCA axes was 86.4 % (Table 3). The first axis was mainly determined by the influence of seawater gradient, which could explain 44.8 % of the total variance in species–environment
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Table 2 Spatial and temporal variations in some dominant species of phytoplankton recovered from Chilika lagoon Season
Phytoplankton taxa
Southern sector Monsoon
Dictyocha sp.a (48), Thalassiothrix longissimaa (12)
Postmonsoon Pre-monsoon
Pleurosigma normaniia (47), Pleurosigma sp. (11) Dictyocha sp.a (45), Synedra sp.abc (25)
Central sector Monsoon
Pleurosigma normaniia (88), Dictyocha sp.a (2.6)
Postmonsoon Pre-monsoon
Anabaena sp.b (21), Pleurosigma sp. (16) Prorocentrum minimuma (16), Synedra sp.abc (10)
Northern sector Monsoon
Anabaena sp. b (23.9), Eudorina sp.b (16.8)
Postmonsoon Pre-monsoon
Trachelomonas sp.b (69.5), Oscillatoria sp.b (4.4) Cylindrospermum sp.b (40.8), Aphanocapsa sp.b (4.5)
Outer channel Monsoon
Nitzschia sp.abc (30), Pleurosigma sp. (12)
Postmonsoon Pre-monsoon
Chaetoceros sp.a (28), Surirella sp.abc (17) Thalassiosira subtilisa (20), Pseudonitzschia pungensa (10)
Number in the parenthesis of each species denotes percentage abundance of that particular species. The preferred salinity regime (marine, freshwater, brackish) for species based on the available literature is also included. Many of the major species, for example Thalassiothrix longissima, Pleurosigma normanii, Pleurosigma sp. Anabaena sp., Eudorina sp. Trachelomonas sp., Oscillatoria sp., Nitzschia sp., Chaetoceros sp., and Pseudonitzschia pungens, are cosmopolitan in their distribution, while other species such as Prorocentrum minimum and Thalassiosira subtilis are restricted to tropical and temperate regions a
Marine
b
Freshwater
c
Brackish
relationship (r=0.80). Salinity (r=−0.65) and pH (r= 0.39) were found to be strong contributors to the first CCA axis. The second axis explained 23.5 % of the variance in the species–environment relationship (r= 0.68) and was mainly determined by light availability. Transparency (r=0.31) and turbidity (r=−0.29) were the strongest contributors to the second CCA axis. The third axis explained 18.1 % of the variance in the species– environment relationship (r=0.60), and silica contents (r=0.31) were the strongest contributors to the third CCA axis.
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In Chilika lagoon, northern sector where river discharge occurs had low salinity and high DO and silica. Euglenophyta, Chlorophyta, and Cyanophyta were more abundant in northern sector (Fig. 3a). Southern sector being brackish in salinity and having water of high transparency was mostly represented by Chrysophyta and Dinophyta. Outer channel had the highest salinity and turbidity level. Bacillariophyta showed higher abundance in outer channel and central sector, where salinity levels were comparatively higher than the other sectors of the lagoon. Among central sector stations, CS3 showed more similarity with stations from the northern sector. This denoted that CS3 was more influenced by river discharge than seawater intrusion based on its closer proximity to the northern sector. Seasonal data analysis based on CCA showed that monsoon had the largest variation in species abundance and environmental variables (Fig. 3b). A strong positive correlation was observed between phytoplankton density and salinity during pre-monsoon (r=0.382, p
