Seasonal variation in optically active substances at a coastal site along western Bay of Bengal
- 64 Downloads
Optically active substances (OAS) such as chlorophyll-a (chl-a), chromophoric dissolved organic matter (CDOM) and total suspended matter (TSM) play significant role in health assessment of aquatic ecosystem. Temporal variability in OAS plays important role in modulating coastal water ecology. This demand for continuous monitoring of OAS in coastal waters. The present study highlights on temporal variability of OAS off Gopalpur, a coastal site along the north-western Bay of Bengal. The OAS were found to be having strong seasonal influence apart from large variability in concentration. Chl-a concentration showed fourfold variability (0.03–12.29 mg m−3) with seasonal trend of pre-monsoon > post-monsoon > monsoon. Absorption due to CDOM at 440 nm (aCDOM440) varied between 0.02 and 4.48 m−1 following seasonal trend of pre-monsoon > monsoon > post-monsoon. TSM concentration was ranged within 0.1–28.21 mg l−1 showing maximum during monsoon and minimum during post-monsoon season. The higher concentration of chl-a and aCDOM440, during pre-monsoon season, was predominantly due to ecosystem disrupting red tide event of Noctiluca bloom during pre-monsoon season of 2014. The high load of TSM during monsoon was due to increased river influx attributed to upstream precipitation. There was no significant relation observed among the OAS indicating that multiple sources of OAS in optically complex waters of the north-western Bay of Bengal. The study provides understanding on long-term variations in OAS which is essential for development or tuning of bio-optical algorithms for accurate remote estimation of geophysical products.
KeywordsChlorophyll-a Total suspended matter aCDOM440 South-west monsoon Bay of Bengal
The Optically Active Substances (OAS) in the ocean water column are principally chlorophyll-a (chl-a), Coloured Dissolved Organic Matter (CDOM), and Total Suspended Matter (TSM) . The differential variability in concentrations of OAS in the water column significantly determines the accuracy of ocean colour remote sensing especially in optically complex case-2 waters . Therefore, region specific understanding on long-term variation of OAS is mandatory for development or tuning of well performing bio-optical algorithms for accurate remote estimation of geophysical products. In addition, the time-series observation of OAS discerns ambient water quality and ecosystem status of food chain.
In general, phytoplankton are responsible for ~ 50% of global primary production, therefore play a key role in global biogeochemical cycle. Chl-a is the dominant light harvesting pigment in phytoplankton and widely considered as proxy of phytoplankton biomass. Hence, concentration of chl-a indicates the ecosystem health. In general, phytoplankton growth is controlled by numerous factors viz. availability of nutrients, light, salinity, temperature and physical conditions . Sometimes, phytoplankton growth occurs with abrupt increase in cell density and results massive blooms. Many regions of World Ocean are experiencing recurring episodes of mono-specific phytoplankton blooms. In general ecosystem monitoring, accounting the phytoplankton bloom is most important due to their adverse effects on water quality .
CDOM is the fraction of dissolved organic matter that absorbs light in the blue region of the electromagnetic spectrum [32, 36]. CDOM usually composed of humic substances, fulvic acids and other polymeric organic matter . Fresh water influx from rivers and terrestrial run-off enriched with organic matters serves as important sources of CDOM to coastal waters. However, phytoplankton debris also contributes significantly to the CDOM pool in coastal and estuarine waters [16, 29]. In general, absorption of blue light by CDOM overlaps the phytoplankton absorption peak near 440 nm, resulting in a competition between CDOM and phytoplankton for light in this region of the visible spectrum . Thus, introduces error while retrieving phytoplankton biomass (i.e. chl-a) through ocean colour remote sensing [12, 23]. A number of physico-chemical-biological processes for example, dilution of terrestrially-derived CDOM, photochemical bleaching, bacterial degradation and autochthonous production of CDOM by plankton influence the optical properties and distribution of CDOM in coastal waters .
TSM mainly represents the inorganic suspended material in the water column and regarded as one of the important OAS due to major role in light attenuation. In general, TSM concentration determines water clarity . The presence of large concentrations of TSM in water affects the penetration of light into the water column, causes decrease in productivity of aquatic vegetations, which subsequently alter the health and quality of the water body. In context of ocean colour remote sensing, higher concentration of TSM in the ambient medium results poor performance of atmospheric correction schemes .
In context of OAS studies, coastal waters off Gopalpur in the north-western Bay of Bengal owes pivotal importance due to riverine influence, terrigenous runoff, recurring phytoplankton blooms etc. . Although many of studies have been carried out to understand the variability of chl-a, TSM and nutrients in this region, no comprehensive monitoring study carried out on the OAS including CDOM [1, 2, 3, 4, 5, 6, 7]. The present study is focused on understanding the temporal variability of OAS off Goplapur, a coastal site along the north-western Bay of Bengal.
2 Materials and methods
2.1 Study site
2.2 Sampling and analytical methodology
In situ seawater samples were collected onboard a fishing trawler from coastal waters of Gopalpur, during several scientific surveys (84), between October 2010 and March 2017. At each station, seawater samples were collected using a Niskin sampler for estimation of chl-a, TSM and CDOM. The group of months March-June, July–October and November-February represent seasons as pre-monsoon, monsoon and post-monsoon, respectively.
Chl-a was estimated following Strickland and Parsons . A known volume of water samples were vacuum filtered through 47 mm Glass Fibre Filters (GF/F). The matter retained on the filter was flooded with 90% acetone and kept overnight in dark for pigment extraction. Subsequently, the samples were centrifuged and optical densities of the supernatant were measured (at 630 nm, 645 nm and 665 nm) using a UV–visible spectrophotometer (Jasco™ double beam V-650).
TSM concentration was determined gravimetrically by filtering a known volume of water sample through 0.45 μm pre-weighed membrane filter paper. Subsequent to filtration, the filter paper was re-weighed using well calibrated electronic balance to estimate TSM concentration .
3 Results and discussion
The magnitude of TSM was ranged between 0.1 and 28.21 mg l−1. TSM values deviated to 34% with respect to normal trend. The TSM values were largely distributed over the range of 0.10–19.40 mg l−1. Two patches of high TSM concentration were also observed at 23.70 mg l−1 and 28.21 mg l−1 during monsoon months September and August, respectively attributed to precipitation induced river/terrigenous discharge. The maximum frequencies in distribution of TSM were observed within 4.10–5.90 mg l−1 (25.5% sample), 6.10–7.84 mg l−1 (24.2% sample) and 8.03–9.90 mg l−1 (29.93% sample) (Fig. 2b).
Several studies have been performed in the study area that recorded similar concentration of chl-a and TSM in corroboration with the present study. The concentration of chl-a was observed within magnitudes reported during earlier observations (0.12–10.05 mg m−3) in the study region . Most of the times, sporadic higher values of chl-a and TSM was observed in association with phytoplankton blooms [5, 27, 34].
The magnitude of aCDOM440 varied between 0.02–4.48 m−1. The maximum frequencies of aCDOM440 largely varied between 0 and 0.44 m−1 (94.9% of samples) (Fig. 2c) ~ 100% deviation was observed in the distribution of aCDOM440 with respect to normal Gaussian distribution. A patchy distribution of aCDOM440 also depicted from the frequency distribution with high values within 3.5–4.48 m−1 (Fig. 2c). Higher magnitude of aCDOM440 have been also reported from Swan River Estuary (3.50 m−1), Tamar Estuary (3.63 m−1), Mahakam Delta (5.25 m−1), Chesapeake Bay-Delaware Bay (2.0–5.0 m−1) and Mississippi Sound/Mobile Bay (3.13–4.27 m−1) [8, 15, 20, 25]. A thorough perusal of available literature confirmed no previous study on aCDOM440 in the study area in order to compare the range of variability. The present study is the first report of aCDOM440 and slope parameter in the study area. However, Mishra et al.  observed absolute concentration of CDOM as 51.18 µg l−1 in the study area. Due to paucity of earlier observations, studies carried out on aCDOM440 in nearby locations of the western Bay of Bengal were compared with the present study. Coastal waters of Vishakhapatnam, on the southern side of the study area was observed with comparatively lower range of aCDOM440 (0.120–0.252 m−1) . aCDOM440 values ranging between 0.1002 and 0.6631 m−1 have been reported in coastal waters off West Bengal, north of present study area . The comparative higher and lower values of aCDOM440 in view of the present study could be attributed to the degree of estuarine influence and terrigenous flux received by individual areas . The magnitude of spectral slope of aCDOM440 varied within 0.001–0.015 nm−1. The peak frequency of spectral slope of aCDOM440 varied within 0.008–0.01 (26.75% samples) and 0.01–0.012 (43.94% samples) (Fig. 2d). The spectral slope of aCDOM440 deviated to 21% with respect to normal.
The occurrence of bloom in the Bay of Bengal is influenced by several physico-chemical and biological processes [17, 31]. In general, phytoplankton blooms were recorded during pre-monsoon season in the study region [5, 34]. Local upwelling induced nutrient recharge of water column triggers recurring algal bloom in the study area . In addition, stable water temperature and muggy weather without rain are considered as conducive conditions for algal bloom, especially proliferation of N. scintillans in the study area . The seasonal trend of chl-a was observed as pre-monsoon > post-monsoon > monsoon over the study period. The highest concentration of chl-a (12.29 mg m−3) was observed during pre-monsoon attributed to intense bloom of N. scintillans. The monsoon season was observed with lowest magnitude of chl-a (3.89 mg m−3) (Fig. 3a). Freshwater influx due to monsoonal precipitation, higher river discharge and cloud cover retards phytoplankton growth during monsoon period . After withdrawal of south-west monsoon, chl-a concentration was observed higher (4.78 mg m−3) in comparison to monsoon. Increase in water column transparency, reduction in cloud cover and availability of nutrients introduced during previous season (monsoon) could have fuelled phytoplankton growth during post-monsoon.
The other important OAS, TSM concentration (monthly average) varied from 5.59 to 12.23 mg l−1 during the study period (Fig. 3b). The seasonal rank order of TSM concentration was observed as monsoon > pre-monsoon > post-monsoon. Influx of inorganic matter to the coastal water attributed to precipitation induced river and terrigenous runoff during south-west monsoon resulted in higher concentration of TSM (28.21 mg l−1). Despite lower river and terrigenous run off during pre-monsoon season, higher values of TSM during pre-monsoon (maximum 19.4 mg l−1) signified local perturbations. As like chl-a, increased values of TSM was also observed during pre-monsoon (April 2014) in association with the red tide . TSM concentration varied within 3.2–15.7 mg l−1 during post-monsoon period. Decrease in land runoff and stabilization of water column during post-monsoon could have resulted comparative decline in TSM.
The distribution of aCDOM440 was more dynamic at temporal scale in comparison to other OAS viz. chl-a and TSM (Fig. 3c). At temporal scale, monthly average magnitude of aCDOM440 varied between 0.07 and 1.44 m−1. The highest value (0.02–4.48 m−1) was encountered during pre-monsoon (April), whereas lowest magnitude (0.02–0.4 m−1) during post-monsoon (November). The higher absorption of CDOM during March and April substantiated the higher values of aCDOM440 in the pre-monsoon period. Seasonal variability of aCDOM440 followed the rank order of pre-monsoon > monsoon > post-monsoon. Higher magnitude of aCDOM440 during pre-monsoon season could be sourced from the co-prevailing higher concentration of phytoplankton biomass (i.e. chl-a) [14, 33]. In general, phytoplankton degradation and bacterial metabolism contribute significantly to CDOM magnitude in the ambient medium . The higher value of aCDOM440 was observed during the pre-monsoon season of 2014 in association with red Noctiluca scintllans bloom. The degraded matter of the bloom could have resulted with increased values of aCDOM440.
The magnitude of aCDOM440 was ranged within 0.06–0.44 m−1 during monsoon period. In contrast to the present observation, the seasonal trend of aCDOM440 was observed highest in monsoon season and least in other non-monsoon seasons in coastal waters off West Bengal, north of present study area [13, 14]. The difference in aCDOM440 variation pattern between these two locations could be attributed to the effect of pre-monsoon phytoplankton bloom. The monthly mean of spectral slope of CDOM varied between 0.007 and 0.012 nm−1 (Fig. 3d). Lower range of variation in spectral slope of CDOM was observed during different monsoon months while higher during pre-monsoon months. In general, slope parameter in context of CDOM deciphers the source. The higher and lower ranges of variation in slope indicate autoconthous and alloconthous origin of CDOM, respectively . Das et al.  have reported spectral slope of CDOM ranged within 0.007–0.0229 nm−1 in coastal water of West Bengal (north of present study area). During a study in coastal water off Visakhapatanam (south of present study area), Pandi et al.  have reported spectral slope of CDOM from 0.009 to 0.020 nm−1. The range of spectral slope of CDOM observed during the present study (0.001–0.015 nm−1) is concomitant to the studies mentioned above.
The magnitude of chl-a, TSM and aCDOM440 collectively determines the inherent optical properties of ambient medium. In general, CDOM is a byproduct of phytoplankton and/or from terrestrial input in ocean. Hence, CDOM absorption may be related to phytoplankton biomass . Higher magnitude of CDOM was also earlier reported in vicinity of the study area with no significant relation with chl-a . Therefore, river influx/terrestrial run off could have played major role in input of CDOM to coastal waters . No significant relation in variability of aCDOM440 with chl-a as well as TSM was also observed in coastal waters off West Bengal, north of the study area attributed to river influx . In addition, no relation in trend of aCDOM440 and slope indicated complex nature of CDOM dynamics in the study area resulting difficulty in source identification. In general, the non-significant relation observed among the OAS indicated multiple sources of OAS in optically complex waters of north-western Bay of Bengal.
The present study reports a comprehensive long-term analysis of OAS (CDOM, TSM, chlorophyll-a) in an ecologically dynamic coastal site along east coast of India (western Bay of Bengal). The outcome of the study is summarized as (1) large range of variability in OAS, (2) seasonality in OAS distribution, (3) riverine/terrigenous influence along with monsoon forcing on OAS dynamics, (4) pre-monsoon preponderance of phytoplankton leading to bloom, (5) upsurge in CDOM magnitude as a consequence of N. scintillans red tide. In general, the study represents the coastal waters off Gopalpur as an optically complex ecosystem suggesting development of region specific ocean colour models for satellite retrieval of OAS.
The present study was financially supported by SATellite Coastal and Oceanographic REsearch (SATCORE) programme coordinated by Indian National Centre for Ocean Information Services (INCOIS). The authors sincerely acknowledge Director, INCOIS for his support and encouragement. The first author (CP) is thankful to Council of Scientific & Industrial Research (Government of India) for Senior Research Fellowship. This is INCOIS contribution No. 353.
Compliance with ethical standards
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
- 1.Baliarsingh SK, Chandanlal P, Lotliker AA, Suchismita S, Sahu KC, Srinivasa Kumar T (2015) Biological implications of cyclone Hudhud in the coastal waters of northwestern Bay of Bengal. Curr Sci 109(7):1243–1245Google Scholar
- 7.Baliarsingh SK, Srichandan S, Naik S, Sahu KC, Lotliker AA, Kumar TS (2015) Seasonal variation of phytoplankton community composition in coastal waters off Rushikulya Estuary, east coast of India. Indian J Geo-Mar Sci 44(4):508–526Google Scholar
- 9.Bukata RP, Jerome JH, Kondratyev AS, Pozdnyakov DV (1995) Optical properties and remote sensing of inland and coastal waters. CRC Press, Boca RatonGoogle Scholar
- 14.Das S, Hazra S, Lotlikar AA, Das I, Giri S, Chanda A, Akhand A, Maity S, Srinivasa Kumar T (2016) Delineating the relationship between chromophoric dissolved organic matter (CDOM) variability and biogeochemical parameters in a shallow continental shelf. Egypt J Aquat Res 42(3):241–248CrossRefGoogle Scholar
- 18.Gouda R, Panigrahy RC (1996) Ecology of phytoplankton in coastal water off Gopalpur. Indian J Mar Sci 25:18–44Google Scholar
- 22.Kowalczuk P, Kaczmarek S (1996) Analysis of temporal and spatial variability of ‘yellow substance’ absorption in the southern Baltic. Oceanologia 38(1):3–32Google Scholar
- 26.Mishra RK, Shaw BP, Das SK, Rao S, Choudhury SB, Rao KH (2003) Spatio-temporal variation of optically active substances in the coastal waters off Orissa from Rushikulya to Dhamra (east coast of India). Indian J Geo-Mar Sci 32(2):133–140Google Scholar
- 27.Mohanty AK, Satpathy KK, Sahu G, Sasmal SK, Sahu BK, Panigrahy RC (2007) Red tide of Noctiluca scintillans and its impact on the coastal water quality of the near-shore waters, off the Rushikulya River, Bay of Bengal. Curr Sci 93(5):616–617Google Scholar
- 31.Prasanna Kumar S, Nuncio M, Narvekar J, Kumar A, Sardesai S, De Souza SN, Gauns M, Ramaiah N, Madhupratap M (2004) Are eddies nature’s trigger to enhance biological productivity in the Bay of Bengal? Geophys Res Lett 31(L07309):1–5Google Scholar
- 38.Strickland JDH, Parsons TR (1972) A practical handbook of seawater analysis, vol 167. Fisheries Research Board of Canada, Ottawa, p 310Google Scholar
- 40.Vinayachandran PN (2009) Impact of physical processes on chlorophyll distribution in the Bay of Bengal. In: Wiggert JD, Hood RR, Naqvi SWA, Smith SL, Brink KH (eds) Indian ocean biogeochemical processes and ecological variability. American Geophysical Union, Washington, DCGoogle Scholar