Diurnal carbon dynamics in a mangrove-dominated tropical estuary (Sundarbans, India)

Journal Pre-proof Diurnal carbon dynamics in a mangrove-dominated tropical estuary (sundarbans, India) Manab Kumar Dutta, Sanjeev Kumar, Rupa Mukherjee, Niharika Sharma, Avanti Acharya, Prasun Sanyal, Ravi Bhusan, Sandip Kumar Mukhopadhyay PII:

S0272-7714(19)30479-2

DOI:

https://doi.org/10.1016/j.ecss.2019.106426

Reference:

YECSS 106426

To appear in:

Estuarine, Coastal and Shelf Science

Received Date: 16 May 2019 Revised Date:

23 September 2019

Accepted Date: 10 October 2019

Please cite this article as: Dutta, M.K., Kumar, S., Mukherjee, R., Sharma, N., Acharya, A., Sanyal, P., Bhusan, R., Mukhopadhyay, S.K., Diurnal carbon dynamics in a mangrove-dominated tropical estuary (sundarbans, India), Estuarine, Coastal and Shelf Science (2019), doi: https://doi.org/10.1016/ j.ecss.2019.106426. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

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Diurnal carbon dynamics in a mangrove-dominated tropical estuary (Sundarbans, India)

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Manab Kumar Duttaa, Sanjeev Kumara*, Rupa Mukherjeea, Niharika Sharmaa, Avanti

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Acharyab, Prasun Sanyalb, Ravi Bhusana, Sandip Kumar Mukhopadhyayb

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a

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*Correspondence to: [email protected]

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Geosciences Division, Physical Research Laboratory, Ahmedabad - 380009. Gujarat, India Department of Marine Science, University of Calcutta, Kolkata - 700019, West Bengal, India b

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Abstract

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Based on a 24 hours of time-series study, we report the effects of a tidal cycle on carbon

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biogeochemistry of a mangrove dominated tropical estuary (the Sundarbans) located in the

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eastern part of India. Salinity, dissolved oxygen, and pH showed clear tidal variability with

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relatively higher values during high tide than low tide. Dissolved inorganic carbon (DIC)

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concentrations varied over a narrow range (1.92 to 2.19 mM) with relatively higher values

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during low tide; reverse trend, however, was noticed for

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4.28 to – 2.21‰). During low tide, along with estuarine mixing, preliminary evidences for

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influences of biogeochemical (such as organic carbon mineralization, sulfate reduction, and

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denitrification) and hydrological processes (porewater exchange) were found on DIC

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dynamics. The

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of the possible sources for DIC. Dissolved organic carbon showed tidal influence during high

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tide with a signal of porewater mediated addition during low tide. Both particulate organic

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carbon and particulate nitrogen concentrations reached the maximum during low tide with

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stable isotopic compositions showing predominantly marine signature along with the

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possibility of biogeochemical modifications within the estuary. Marine water contribution

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together with organic carbon mineralization and possible porewater influx resulted in ~ 214

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µatm higher pCO2 and 1.13 times higher FCO2 during low tide than high tide. On diurnal

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basis, the estuary released ~ 1348 mg CO2 per m2 of surface area to the regional atmosphere.

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CDIC with significant variability (–

CDIC - DIC relationship suggested respiration of marine plankton to be one

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Keywords: carbon cycle, estuary, mangrove, tidal cycle, Sundarbans, India

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1. Introduction

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Estuaries are one of the most dynamic aquatic ecosystems with abundant biodiversity and

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high biological production that receive substantial dissolved and particulate carbon (C),

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nitrogen (N), phosphorus (P), and silica (Si) from rivers (Bianchi et al., 2006). Globally,

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estuaries are characterized as an important source of carbon dioxide (CO2) to the atmosphere

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(~ 0.27 Pg C yr−1; Laruelle et al., 2010), which is a potent greenhouse gas from global climate

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change perspective. The large emission of this biogenic trace gas shows that estuaries are

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hotspot for biogeochemical C transformations.

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Covering around ~ 60 - 75 % of tropical coasts (Clough, 1998), mangroves are one of

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the most productive ecosystems in the world (net primary production ~ 218 ± 72 Tg C yr-1,

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Bouillon et al., 2008) with high organic matter (OM) turnover (Nedwell et al., 1994).

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However, the fate of mangrove derived organic C (OC) is not well understood. Depending

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upon hydrological (tidal amplitude and inundation frequency) and biological processes

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(activity of fauna such as bioturbation by crabs) within the mangroves, significant export of

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OC to the adjacent estuary has been reported (e.g., Twilley, 1985; Dittmar et al., 2001;

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Dittmar and Lara, 2001a). The remaining OC gets buried in the sediment and participates

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further in aerobic mineralization and more complex anaerobic biogeochemical processes in

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surface and sub-surface sediments, respectively. Under oxic condition, mechanisms

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governing OC mineralization and its subsequent partial diffusive emission as CO2 to the

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atmosphere are not well understood. However, CO2 which escapes diffusion gets dissolved in

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porewater and under favorable conditions gets exported to the adjacent estuary and

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subsequently to the continental shelf region. Additionally, the degree of fresh and marine

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waters mixing in a tide dominated estuary also alter its chemical (nutrient levels), biological

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(biodiversity and community compositions of plankton and bacteria etc.), and physical

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(suspended particulate matter levels) properties that may have potential impact on elemental

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biogeochemistry.

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The C and N cycling in estuaries have been extensively studied (e.g., Seitzinger,

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1987; Cifuentes et al., 1988; Liu et al., 2007). Research related to C biogeochemistry in

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tropical settings, particularly in the Indian subcontinent, has also gained momentum in recent

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years (e.g., Mukhopadhyay et al., 2002; Biswas et al., 2004; Sarma et al., 2011; Sarma et al.,

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2012; Dutta et al., 2013; Sarma et al., 2014; Dutta et al., 2015). The prime focus of most of

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these studies has been on biogeochemistry of biogenic trace gases with limited reports on

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multiple parameters related to C cycling (e.g., Bouillon et al., 2003, Ray et al., 2015, 2018;

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Dutta et al., 2019). In recent years, diurnal C biogeochemistry is being widely studied in

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tropical and sub-tropical mangrove-dominated creeks and estuaries to understand the impact

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of ground water (or porewater) exchange from mangroves on coastal C budgets (Bouillon et

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al., 2007a; Maher et al., 2013; Linto et al., 2014; Sippo et al., 2016) along with emissions of

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greenhouse gases (Call et al., 2015; Rosentreter et al., 2018). Despite being home to

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Sundarbans, the largest mangrove ecosystem in the world, limited attempts have been made

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to understand the diurnal C biogeochemistry of the mangrove-dominated estuaries of India

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(Borges et al., 2003). Recent studies attempted to understand diurnal C dynamics in the

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estuaries of Sundarbans through variations in dissolved inorganic carbon (DIC) and partial

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pressure of CO2 (pCO2) (Akhand et al., 2016) along with quantification of C export flux (Ray

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et al., 2018). However, given the spatial vastness of the Sundarbans and paucity of diurnal

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data related to C cycling, understanding of processes operating on a diurnal scale in this

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important ecosystem is still lacking. Therefore, to fill this knowledge gap, the present study

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measured different C cycling related parameters (both dissolved and particulate C) for 24

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hours in one of the major estuaries of the Indian Sundarbans during premonsoon. Since

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earlier studies have demonstrated estuaries of the Sundarbans to be polyhaline during

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premonsoon (Biswas et al., 2004, Dutta et al., 2015), we hypothesize that marine water

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contribution along with biogeochemical and hydrological processes control diurnal C

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dynamics in estuaries of the Sundarbans. To test the hypothesis, we investigated factors

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affecting diurnal variations in [a] DIC and its stable isotopic composition (δ13CDIC), [b]

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dissolved organic carbon (DOC), [c] particulate organic carbon and nitrogen (POC and PN)

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and their stable isotopic compositions (δ13CPOC and δ15NPN), [d] pCO2 and air-water CO2 flux

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(FCO2).

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2 Material and Methods

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2.1 Study area

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Listed as a UNESCO world heritage site, the Sundarbans (Lat: 21o32’- 22o40’N; Long:

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88o05’ - 89oE) is the largest mangrove forest in the world. Situated at the land-ocean

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boundary of the Ganges - Brahmaputra delta and the Bay of Bengal (BOB), the Sundarbans

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cover an area of 10,200 km2 as reserved forest, 41% of which lies in India and the rest in

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Bangladesh. The Indian part of the Sundarbans, known as the Sundarbans Biosphere Reserve

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(SBR), constitutes of 4200 km2 mangrove reserve forest, 1800 km2 estuarine waterways, and

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3600 km2 reclaimed areas. The SBR is crisscrossed by several rivers forming 102 islands

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displaying thick mangrove forest composed dominantly of Avicennia alba, Avicennia marina

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and Avicennia officinalis while Excoecaria agallocha and Ceriops decandra are also found

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scattered. Having semidiurnal tide, the estuaries of Sundarbans (Saptamukhi, Thakuran, and

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Matla; mean depth ~ 6 m) are typically marine dominated with limited anthropogenic inputs

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during monsoon (Dutta et al., 2015). The present time-series observations were conducted at

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the Saptamukhi estuary during premonsoon (Fig.1). The Saptamukhi was chosen due to

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relatively stable conditions for the time-series study compared to other two major estuaries

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(Thakuran and Matla).

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2.2 Sampling and experimental techniques

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Surface water (~ 0.5 m depth) samples were collected in duplicate from a fixed mid-estuary

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location using a Niskin bottle (Oceantest Equipment, Capacity: 5L) from 29th March (14:00)

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to 30th March (13:00) 2017. Times are given as local time (GMT + 5.5 hrs). Different

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parameters measured and techniques used for analyses are presented below.

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2.2.1 Field sampling and on board measurements

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Immediately after sampling, water temperatures and pH were recorded using a thermometer

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(± 0.1 oC) and a portable pH meter (Orion Star A211) fitted with a Ross type combination

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electrode calibrated on the NBS scale (Frankignoulle and Borges, 2001) having

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reproducibility of ± 0.005 pH units. Salinity (± 0.1) and dissolved oxygen (DO; ± 0.1 mg L-1)

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were measured following the Mohr-Knudsen and Winkler titration methods, respectively

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(Grasshoff et al., 1983). For total alkalinity (TAlk), 50 ml of filtered (0.7 µm filters) water

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was titrated in a closed cell using 0.1N HCl following potentiometric titration method

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(Bouillon et al., 2003). Uncertainty for TAlk was ±1 µmol kg-1, when tested with the Dickson

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standard (CRM: Batch 131). For δ18O analysis in water, samples were collected in 60 ml

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HDPE bottles.

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Samples for DIC and δ13CDIC were collected by gently overfilling teflon septa fitted

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glass vials followed by addition of saturated HgCl2 solution to arrest microbial activity. For

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DOC, samples were filtered through pre-weighted and pre-combusted (450 oC for 5 hrs.)

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glass-fiber filters (Whatman GF/F, 0.7 µm) and the filtrates were kept in dark bottles

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followed by H3PO4 addition (Bouillon et al., 2003). The residues on the glass-fiber filters

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were kept for suspended particulate matter (SPM) analyses. Samples for DIC, DOC, and

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SPM were preserved at 4 oC during transportation to the laboratory. Wind velocities at 10 m

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height over the estuary were continuously monitored using a portable weather monitor

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(DAVIS - Vantage Pro2 Plus).

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2.2.2 Laboratory techniques

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The DIC were measured using a Coulometer (Model: UIC. Inc. CM - 5130) (analytical

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uncertainty: ± 0.8%). The δ13CDIC and δ18O in water samples were analyzed using a Gas

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Bench connected to a continuous flow mass spectrometer (Thermo Scientific MAT - 253)

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with analytical reproducibility of < ± 0.10‰ for both. Values of δ13CDIC and δ18O have been

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reported relative to V-PDB (Vienna-Pee Dee Belemnite) and VSMOW (Vienna Standard

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Mean Oceanic Water), respectively. The DOC were estimated by a high-temperature catalytic

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oxidation analyzer (Shimadzu-TOC-L CPH) with analytical reproducibility < 2%.

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The filter papers containing SPM were dried in a hot air oven at 60oC and final

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weights were noted. The SPM concentrations were calculated based on the initial and final

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weights of filter papers and volumes of water filtered. For POC and δ13CPOC analyses, a

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section of filter papers was de-carbonated (by HCl fumes) and analyzed using an elemental

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analyzer (Thermo Scientific - Flash 2000) connected to a continuous flow mass spectrometer

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(Thermo Scientific MAT - 253) via conflo. Similar method was used for PN and δ15NPN

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analyses but without de-carbonation. The analytical reproducibility for δ13CPOC (relative to V-

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PDB) and δ15NPN (relative to AIR-N2) were < ± 0.09‰ and < ± 0.20‰, respectively.

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Uncertainties for POC and PN were <10% for duplicate samples.

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2.2.3 Calculations and flux estimation

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The %DO and apparent oxygen utilization (AOU) were calculated as:

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where, [DO]Eq is the equilibrium DO concentration calculated at in situ temperature and

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salinity (Weiss, 1970) and [DO]Obs is the measured DO concentration. Using carbonic acid

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disassociation constants (widely used for estuarine and marine waters having temperature 0 -

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50 oC and salinity 0 - 50; Millero et al. 2006) and the KHSO4 constant (Dickson, 1990), pCO2

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and Revelle factor (RF) were computed through CO2SYS program (Pelletier et al., 2007) by

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putting temperature, salinity, TAlk, and pH as input variables. Excess dissolved CO2 or free

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dissolved CO2 in excess of atmospheric equilibrium ([CO2*] excess) was calculated as:

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here, [CO2*] is the total free CO2 concentration ([CO2*] = [CO2] + [H2CO3] = α × pCO2; Zhai

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et al., 2005), ‘α’ is the solubility co-efficient of CO2 and pCO2air is the partial pressure of CO2

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in atmosphere. The latest available atmospheric CO2 mole fraction in dry air at Cape Rama,

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India (~ 407 ppm; World Data Center for Greenhouse Gases - https://gaw.kishou.go.jp/) was

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converted to obtain pCO2air using respective vapor pressure. Air - water CO2 fluxes (FCO2 in

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µmol m-2 hr-1) were calculated as:

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where, 'k’ is the wind speed gas transfer velocity, calculated following Raymond and Cole

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(2001) and ∆pCO2 is the air-water gradient of pCO2.

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To decipher the factors influencing diurnal C biogeochemistry in the mangrove-

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dominated estuary, the time-series study was divided into (a) low tide (14:00 - 19:00 on 29th

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March & 2:00 - 7:00 on 30th March) and (b) high tide (20:00 on 29th March - 1:00 on 30th

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March & 8:00 - 13:00 on 30th March; Fig. 2). The tidal conditions were classified based on

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variations in salinity with salinity ≤ 29.5 as low tide and ≥ 29.5 as high tide. Additionally,

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day (6:00 - 17:00) and night (18:00 - 5:00) variability and its coupled interaction with tidal

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variability were also assessed. The sampling period was chosen randomly to capture diurnal

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variation in ambient processes and were not related to specific processes such as spring tide,

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neap tide, etc. For the purpose of discussion, henceforth, low and high tides are designated as

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‘LT’ and ‘HT’, respectively.

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3. Results

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3.1 General parameters

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Water temperatures (26 to 30 oC) showed fluctuation with tidal variability with lower

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temperatures during LT (Fig. 2a). Mean daytime temperature was marginally higher (by ~

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1.33 oC; 28.5 to 30 oC) than night-time (26 to 29 oC), with the sharpest fall between 22:00

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and 4:00 (Fig. 2a). As expected, a clear tidal variability was noticed for salinity with higher

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values during HT (Fig. 2a). Varying within a narrow range, pH (7.91 to 8.09; Fig. 2b), DO

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(6.01 to 6.57 mg L-1; Fig. 2c), and

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trend as salinity.

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3.2 Inorganic and organic carbon

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The DIC (1.92 to 2.19 mM) and DOC (1.31 to 3.44 mg L-1) varied over a narrow range with

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relatively higher value during LT (on average DIC by ~ 0.16 mM and DOC by ~ 0.36 mg L-1)

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than HT (Fig. 3a and 3b). However, δ13CDIC (– 4.28 to – 2.21‰; mean: – 3.04 ± 0.82‰)

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showed prominent fluctuations with tidal variability having relatively lower values during LT

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than HT (Fig. 3c). The night-time mean DIC, δ13CDIC, and DOC showed marginal differences

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(higher by ~ 0.002 mM, ~ 0.015‰, and ~ 0.06 mg L-1, respectively) with daytime.

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Coinciding with pH and DIC, TAlk also varied over a narrow range on a diurnal scale (2.19

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to 2.58 meq L-1; Fig. 3d).

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3.3 Particulate organic matter

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The SPM (238 to 1090 mg L-1, mean = 621 ± 244 mg L-1; figure not shown) and POC (130 to

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508 µM, mean = 315 ± 106 µM; Fig. 4a) varied over a wider range compared to PN (13 to 59

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µM; Fig. 4b). On average, POC and PN were ~ 12 and ~ 21% lower during HT than LT. The

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13

CPOC (– 23.15 to – 21.70‰) and

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O (– 2.04 to – 0.26‰; Fig. 2d) also followed a similar

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NPN (8.71 to 12.20‰) were not significantly linked to 15

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tidal variability (Fig. 4c and 4d) with an anomalously high

NPN (14.75‰) during midnight

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(Fig. 4d). On average, the daytime showed marginally higher POC (by ~ 27 µM) and PN (by

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~ 0.5 µM) in contrast to relatively lower

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night-time.

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3.4 pCO2 and FCO2

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The pCO2 varied from 533 to 918 µatm (mean = 690 ± 129 µatm) with on average ~ 214

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µatm higher pCO2 during LT than HT (Fig. 4e). Daytime pCO2 was marginally lower (by ~

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24 µatm) than night-time. Both [CO2*]

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15.11 µM; FCO2 = 398 to 3364 µmol m-2 hr-1) throughout (Fig. 4f).

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3.5 Statistical Analysis

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A two-way ANOVA was performed to analyze the effects of light-dark (day-night;

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considering photo-dependent processes) and tidal conditions along with their interaction on

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diurnal C biogeochemistry. The analyses showed significant effect of tidal variability on DIC

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CPOC (by ~ 0.25‰) and

excess

15

NPN (by ~ 0.21‰) than

and FCO2 were positive ([CO2*]

excess

= 3.76 to

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and pCO2 (DIC: F = 39.03, p < 0.001; δ13CDIC: F = 86.18, p < 0.001; pCO2: F = 54.22, p <

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0.001) with little impact of light-dark condition (DIC: p = 0.95, δ13CDIC: p = 0.93; pCO2: p =

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0.43) or their (tidal × light-dark) interaction (DIC: p = 0.65, δ13CDIC: p = 0.76; pCO2: p =

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0.89). DOC were significantly linked with tidal variability (F = 5.65, p < 0.05) and tidal ×

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light-dark interaction (F = 12.19, p < 0.01) with no significant effect of light-dark condition

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alone (p = 0.70). On the contrary, variabilities in particulate organic matter was not

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significantly associated with either tidal (POC: p = 0.37; PN: p = 0.14; δ13CPOC: p = 0.25;

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δ15NPN: p = 0.85) or light-dark (POC: p = 0.55; PN: p = 0.92; δ13CPOC: p = 0.14; δ15NPN: p =

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0.69) conditions. Overall, these analyses emphasized effectiveness of tides on diurnal C

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biogeochemistry.

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4. Discussion

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4.1 Factors controlling physicochemical parameters

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The time series study indicated the system to be marine dominated with marine contribution

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ranging from ~ 74 - 88% (considering typical marine and freshwaters salinities as 35 and 0,

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respectively), corroborating the previously reported polyhaline nature of the estuaries of

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Sundarbans (Dutta et al., 2015). Overall, the estuary was well oxygenated (DO%: ~ 88 - 98).

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However, sharp declines in DO and pH were noticed during LT, which might be linked with

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higher aerobic OM mineralization (see pCO2 section) and H+ influx during LT, respectively.

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Another reason could be DIC enriched (Dutta et al., 2019) and O2 depleted (reduction-

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oxidation potential (Eh): −111.4 ± 6.78 and −186.7 ± 24.6 mV for surface and 25 cm deep

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mangrove sediment, respectively; Dutta et al., 2013, 2017) porewater discharge across

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intertidal mangrove sediment - estuary interface during LT.

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The

18

O - salinity relationships revealed conservative mixing during LT (r2 = 0.79, p

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< 0.001) which was missing during HT (r2 = 0.02, p = 0.66). The source of marine water at

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the Sundarbans is evident (i.e., coastal BOB), whereas possibility for multiple sources of

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freshwater exists, including river runoff, precipitation, and groundwater discharge. Being pre-

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monsoon, influence of precipitation as freshwater input was minimal. Extrapolating

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salinity relationship to typical marine and fresh water end member salinities (mentioned

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earlier),

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6.55‰ and – 0.35‰, respectively. The calculated

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the range reported for the river Ganges during non-monsoon period (– 10 to – 6‰; Gajurel et

18

18

O-

O for fresh and marine water end members during LT were calculated as ~ – 18

O for freshwater end member fell within

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al., 2006). The Ganges is connected to the estuaries of the Indian Sundarbans through

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different channels and tributaries and forms a major source of freshwater.

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4.2. Diurnal DIC dynamics

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The DIC and

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2018) and pristine mangrove creeks elsewhere in the world (Bouillon et al., 2007a, Maher et

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al., 2013). DIC and

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salinity: r2 = 0.85, p < 0.001;

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salinity: r2 = 0.015, p = 0.90;

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indicated relatively greater control of estuarine mixing on DIC during LT than HT. The

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impacts of in situ biogeochemical processes, such as CaCO3 dissolution/precipitation,

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photosynthesis, OM respiration, and CO2 outgassing on diurnal DIC can be investigated

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using a two end member mixing model (Alling et al., 2012). However, it could not be applied

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here due to narrow salinity range. Alternatively, TAlk - DIC relationship (Linto et al., 2014,

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Borges et al., 2018) has been explored to decipher the same.

13

CDIC were in the range reported previously for the Sundarbans (Ray et al., 13

CDIC were significantly correlated with salinity during LT (DIC 13

CDIC - salinity: r2 = 0.90, p < 0.001) but not during HT (DIC 13

CDIC - salinity: r2 = 0.017, p = 0.68) (Fig. 5a & 5b). This

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During LT, TAlk - DIC were significantly correlated (r2 = 0.43, p < 0.05; Fig. 5c)

287

with slope of 0.89. However, the relationship was not significant during HT (r2 = 0.16, p =

288

0.19; Fig. 5d). Our estimated slope during LT existed within the theoretical TAlk/DIC slopes

289

for denitrification (0.8) and sulfate reduction (1; Krumins et al., 2013), indicating their

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potential impact on carbonate chemistry. Being an oxygenated estuary, the signal for

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anaerobic OM metabolism during LT may come from adjacent anoxic intertidal mangrove

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sediment via porewater exchange due to tidal pumping (Dutta et al., 2013, 2015). Generally,

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mangrove porewater contains high TAlk and DIC due to coupled interaction between aerobic

294

and anaerobic OM metabolisms (Ovalle et al., 1990; Alongi et al., 1998, 2001; Kristensen et

295

al., 2000). Although premonsoon porewater DIC data are not available, a recent study on the

296

Sundarbans confirmed DIC enriched porewater (~13,425 mM) together with porewater-

297

estuary DIC exchange flux of ~ 770 mmol m-2 d-1 during postmonsoon (Dutta et al. 2019). On

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average, higher DIC and TAlk during LT (by ~ 0.16 mM, ~ 0.05 meq L-1, respectively) than

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HT provided preliminary evidence for porewater mediated DIC and TAlk additions to the

300

estuary. However, a comprehensive study in this regard is desirable to understand the role of

301

porewater exchange vis-à-vis different processes in the ecosystem.

302 303

The

13

CDIC - DIC relationships (LT: r2 = 0.86, p < 0.001; HT: r2 = 0.02, p = 0.63; Fig.

5e) supported the effectiveness of OM respiration on DIC during LT. Simultaneously,

304

following Bouillon et al. (2003), C isotopic composition of added DIC via respiration

305

(δ13CRES) and contribution of OM respiration on DIC during LT were estimated as ~ – 15‰

306

and ~ 19 - 28%, respectively. The estimated δ13CRES fell within the range of δ13C of C4 plants

307

(– 9 to –17‰) and closer to marine plankton (~ – 18 to – 22‰). Since no signature of a C4

308

plant was found in the Indian Sundarbans, it was likely that marine plankton was the possible

309

source for DIC thorough respiration.

310 311

4.3 Diurnal variations in DOC

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The diurnal DOC levels were comparable with earlier reports in the Sundarbans (Ray et al.,

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2015, 2018). DOC exhibited non-conservative behavior during LT (DOC - salinity: r2 = 0.02,

314

p = 0.62) but conservative during HT (DOC - salinity: r2 = 0.32, p = 0.05) (Fig. 6a). The

315

moderately negative DOC - salinity relationship during HT suggested marine water (DOC in

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BOB ~1.05 mg L-1, Dutta et al., 2010) mediated DOC dilution on a diurnal scale. However,

317

in situ biogeochemical and hydrological processes (like porewater exchange) together with

318

photo-oxidation within the mangrove system can also potentially affect DOC dynamics.

319

Barring three data points with low DOC and pCO2 (as marked in Fig. 6b), DOC

320

showed a significant negative relationship with pCO2 during LT (r2 = 0.88, p < 0.001; Fig.

321

6b), which was missing during HT (r2 = 0.11, p = 0.29). The negative relationship highlighted

322

decreasing aerobic bacterial activity despite increasing DOC, suggesting presence of

323

refractory DOC.

324

phytoplankton production on DOC (Wangersky, 1978), lack of direct primary production

325

measurements limited us to evaluate its impact on DOC. The two-way ANNOVA analysis

326

together with small variability between mean day and night-time DOC (~ 0.06 mg L-1)

327

confirmed weak DOC photo-oxidation (i.e., weak light-dark effect). This may be linked to an

328

unstable estuarine condition (Richardson number < 0.14) favoring intensive vertical mixing

329

with longitudinal dispersion coefficients of 784 m2 s−1 in the estuaries of Sundarbans

330

(Sadhuram et al., 2005; Goutam et al., 2015). Such an unstable condition was not conducive

331

for DOC - POC interconversion (inter-conversion via dissolving and flocculation) as well,

332

which was evident from DOC - POC relationships (LT: r2 = 0.005, p = 0.83; HT: r2 = 0.03, p

333

= 0.58; Fig. 6c). There was higher average DOC during LT than HT (by ~ 0.36 mg L-1),

334

suggesting possibility of DOC addition via porewater but we do not have strong independent

335

evidence.

Although

contradictory results

existed

vis-à-vis

importance of

336

The DOC contribution to TOC (= DOC + POC; 22.6 - 53.1%) was lower than other

337

mangrove ecosystems (Bouillon et al., 2007b). In mangroves, litter is reported to leach ~ 30%

338

within initial 9 days of degradation (Camilleri and Ribi, 1986) with efficient transformation

339

to DOC and further into microbial biomass (Benner et al., 1986). However, DOC < POC (~

340

88% cases) suggested limited impact of litter leaching on diurnal DOC variability.

341

Additionally, DOC can be supplied by bacteria, ciliates, flagellates as well as due to release

342

from zoo-plankton faeces and dead organisms (Wangersky, 1978) during degradation.

343

However, we do not have data to quantify individual contributions of the above-mentioned

344

sources in the estuary.

345

4.4 Diurnal particulate organic matter dynamics

346

The diurnal SPM as well as POC and PN contents in this estuary were relatively higher than

347

previously reported (Ray et al., 2015). The SPM distribution was salinity independent (LT: r2

348

= 0.04, p = 0.52; HT: r2 = 0.02, p = 0.63; figure not shown) suggesting limited influence of

349

fresh and marine waters mixing on diurnal SPM variability. Therefore, the observed wide

350

diurnal variability in SPM might be linked to in situ physical (churning of subtidal sediments

351

during vertical mixing; Dutta et al., 2015) and hydrological (tidal amplitude associated with

352

washout area of mangroves as well as inundation frequency) processes. The contributions of

353

POC and PN to SPM were 0.53 - 0.81% and 0.06 - 0.09%, respectively.

354

Sources of OM in an estuary may be traced by the C/N ratios and isotopic signatures.

355

Due to a masking effect by large stock of sediments, it may not be possible to identify

356

original sources of OM in a turbid estuary every time. So, potential modification of OM may

357

be deciphered through the proxies mentioned above (Middelburg and Herman, 2007, Sarma

358

et al., 2014). Our C/N values (8.1 - 12.4) suggested particulate OM contribution from riverine

359

particles (~ 8.1 - 12.9) and soils (~ 9 - 12) along with possible contribution via marine

360

plankton (~ 7) (Hedges and Mann, 1979; Lee and Fuhrman, 1987; Ittekkot and Zhang, 1989;

361

Matson et al., 1990; Bouillon et al., 2002; Goni et al., 2003). However, δ13CPOC and δ15NPN

362

indicated a predominantly marine signature (δ13C ~ – 18 to – 22‰, δ15N ~ 3 - 12‰; Smith

363

and Epstein, 1971; Hedges et al., 1997; Zhang et al., 1997; Dehairs et al., 2000; Bouillon et

364

al., 2002, Maya et al., 2011) throughout, corroborating our hypothesis of marine influence.

365

Despite being a mangrove dominated estuary, relatively lower C/N together with higher

366

δ13CPOC and δ15NPN compared to mangroves (C/N for Sundarbans mangrove: ~27, δ13CMangrove

367

~ – 27‰, δ15NMangrove ~ – 1.5 to 3.2‰, Muzuka et al., 2006, Miyajima et al., 2009, Ray et al.,

368

2015)

suggested

possibility

of

particulate

OM

modification

(Middelburg

and

369

Nieuweuwenhuize, 1998, Middelburg and Herman, 2007; Sarma et al., 2014), which is likely

370

to be aerobic in this oxygenated estuary.

371

Our δ15NPN (8.71 - 14.75‰) were higher than other Indian estuaries (northern

372

estuaries: 0.7 - 5.8‰, southern estuaries: 5 - 10.3‰; Sarma et al., 2014), which could be

373

linked to possible nitrification. During nitrification, preferential 15

+

14

N uptake (Mariotti et al.,

15

374

1984) results in N enriched NH4 pool, which leads to higher δ NPN when incorporated by

375

algae (Mariotti et al., 1984; Cifuentes et al., 1988, 1989) and heterotrophic bacteria (Caraco

376

et al., 1998; Middelburg and Nieuwenhuize, 2000a, 2000b). High δ15NPN due to nitrification

377

has been reported worldwide (Schelde estuary: 24‰, Delaware estuary: 18‰; Cifuentes et al.,

378

1989, Middelburg and Nieuwenhuize, 1998). Relatively lower NH4+ (0.28 - 2.67 µM; Dutta

379

et al., unpublished data) than other Indian estuaries (Sarma et al., 2010, 2014; Krishna et al.,

380

2016) coupled with well oxygenated water (DO: 94 ± 4%) suggested possibility of

381

nitrification. Also, NO3- can be an important N substrate for heterotrophic bacteria

382

(Middelburg and Nieuwenhuize, 2000b), which results in

383

partial assimilation (Caraco et al., 1998). The uptake of such 15N enriched NO3- by algae can

384

also result in high δ15NPN.

15

N enriched NO3- pool due to

385 386

4.5 Diurnal variations in pCO2

387

In estuaries, pCO2 levels are principally regulated by hydrological and biogeochemical

388

processes. In addition, for a mangrove dominated estuary, inputs via mangroves and water

389

residence time also play a significant role. The significant negative correlation was found

390

between diurnal pCO2 and salinity during LT (r2 = 0.71, p < 0.001) but not during HT (r2 =

391

0.002, p = 0.88) (Fig. 7a). This inverse relationship during LT may be linked with lower CO2

392

buffering (i.e., high pCO2) relative to DIC inputs with decreasing salinity, which was

393

supported by higher estimated RF during LT (11.8 – 14.9) than HT (10.7 - 11.6). Also,

394

preliminary evidence for existence of a mechanism resulting into simultaneous CO2

395

production and DO consumption (i.e., mineralization) during LT was observed from inverse

396

relationship between pCO2 - %DO (r2 = 0.44, p < 0.05; figure not shown). This was further

397

confirmed by a positive relationship between [CO2*]

398

0.30AOU; r2 = 0.53, p < 0.01; Fig.7b) as well as δ13CDIC study (see section 4.2). However,

399

our slope (0.30) was significantly lower than that theoretically predicted for the Redfield

400

respiration in HCO3- rich environment, like the Sundarbans (∆CO2 / –∆O2 = 124/138 = 0.90,

excess

and AOU ([CO2*]

excess

= 6.035 +

401

Zhai et al., 2005), suggesting relatively less CO2 production than expected. This may be

402

attributed to production of low molecular weight OM during mineralization instead of final

403

product (CO2). No strong evidence of productivity was found as average difference between

404

night and daytime pCO2 was small (~24 µatm), which was also reflected in two-way

405

ANNOVA analysis. Taken together, dominance of OM respiration over productivity

406

suggested the estuary to be net heterotrophic (Biswas et al., 2004, Dutta et al., 2015).

407

Additionally, possibility existed for CO2 addition via porewater exchange based on relatively

408

higher pCO2 during LT than HT (by ~ 214 µatm).

409

Throughout positive [CO2*] excess indicated the estuary to be a potential source of CO2

410

to the regional atmosphere on diurnal scale. The degree of CO2 emission, however, depends

411

upon [CO2*]

412

values in estuaries are highly variable and its parameterizations as a function of wind speed

413

are site-specific (Borges et al., 2018). Here, we have calculated ‘k’ values based on Raymond

414

and Cole (2001), which provides the minimal values for ‘k’ (Borges et al., 2018). Therefore,

415

our estimated FCO2 may be the conservative estimate of diurnal CO2 flux. Due to

416

variabilities in ‘k’ and pCO2, FCO2 were highly variable on diurnal scale with on average

417

~1.13 times higher during LT than HT. Mean FCO2 during the study was 1276 ± 667 µmol

418

m-2 hr-1 (~ 1348 mg CO2 m-2 d-1), much higher than earlier report from the Thakuran estuary

419

(23.62 - 29.7 mg CO2 m-2 d-1; Akhand et al., 2012) but lower than other Indian mangroves

420

(Borges et al., 2003). Inter-estuary variability in FCO2 links with variability in pCO2 levels as

421

well as geographic locations of the sampling sites, which affects ‘k’ and, in turn, flux.

excess

and gas transfer velocity (k) across water-atmosphere interface. The ‘k’

422

In general, on diurnal scale, basic estuarine parameters (salinity, DO, δ18O, and pH)

423

were observed to be relatively higher during HT, whereas C cycle associated parameters were

424

higher during LT. Concurring with our hypothesis, these parameters were largely affected by

425

marine influence along with biogeochemical and hydrological processes. No significant

426

effects of freshwater input as well as light-dark condition were found. Overall, the study

427

highlighted the variabilities in C cycle related parameters for only one diurnal cycle at a

428

remote location in a mangrove-dominated estuary. To gain a deep insight into the processes

429

and fully constrain the variabilities, such studies at more locations and diurnal cycles are

430

desirable.

431 432 433 434

435 436 437 438

5. Conclusions

439

Diurnal carbon biogeochemistry was studied in a mangrove dominated tidal estuary of the

440

Indian Sundarbans. Evidence for strong influence of estuarine mixing was found on DIC and

441

δ13CDIC during low-tide, whereas marine water mediated dilution was observed during high

442

tide for DOC. During low tide, influences of aerobic organic matter mineralization,

443

denitrification and sulfate reduction on DIC together with possible DIC and DOC

444

contributions via porewater were highlighted. Being not controlled by tidal effect, both POC

445

and PN showed predominantly marine signature throughout along with possibility of

446

biogeochemical transformations. Higher pCO2 were observed during low tide, which was

447

linked to tidal fluctuations, organic carbon mineralization, and possibly porewater influx.

448

Throughout positive FCO2 confirmed net emission of the CO2 from the estuary on diurnal

449

scale. The two-way ANNOVA analysis of the data predominantly showed the effect of tidal

450

variability only on dissolved carbon with additional impact of tidal × light-dark interaction on

451

DOC.

452

Author contributions

453

MKD and SK designed the study. AA and PS helped in sample collection and analysis of

454

some basic parameters. MKD together with RM and NS analyzed the samples. MKD and SK

455

interpreted the data and prepared the manuscript. RB and SKM provided facilities to analyze

456

DIC and DOC, respectively.

457

Acknowledgements

458

M.K.D is thankful to postdoctoral fellowship program of the Physical Research Laboratory.

459

Funding for this work was provided by Indian Space Research Organization - Geosphere

460

Biosphere Program (ISRO-GBP). Authors are thankful to Sundarbans Biosphere Reserve for

461

permission to carry out the field trip. Thanks to Rishmita Mukherjee, Sneha Bakshi, Vandana

462

Kumari Gupta, and Sayan Dey for help during the field trip. Authors are thankful to the

463

associate editor and two anonymous reviewers for constructive comments.

464

465 466 467

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707 708 709 710 711 712

713 714 715 716 717 718 719

720 721 722 723 724 725

726 727 728

Fig.1: Sampling location during the time series study.

729 730

Fig.2: Diurnal variations in (a) water temperature, (b) pH, (c) %DO, and (d) δ18O with

731

salinity. Here, ‘HT’ and ‘LT’ indicate high and low tides, respectively.

732 733

Fig.3: Diurnal variations in (a) DIC, (b) DOC, (c) δ13CDIC, and (d) TAlk with salinity. Here,

734

‘HT’ and ‘LT’ indicate high and low tides, respectively.

735

736 737

Fig.4: Diurnal variations in (a) POC, (b) PN, (c) δ13CPOC, (d) δ15NPN, (e) pCO2, and (f) FCO2

738

with salinity. Here, ‘HT’ and ‘LT’ indicate high and low tides, respectively.

739 740

741 742 743 744 745 746 747 748

Fig.5: Variabilities of (a) DIC - salinity, (b) δ13CDIC - salinity, (c) TAlk - DIC during low tide (here, RE = regression line, CP = carbonate precipitation, OMR = organic matter respiration, DN = denitrification, SR = sulfate reduction, CD = carbonate dissolution, MR = Mn reduction and IR = Fe reduction), (d) TAlk - DIC during high tide, and (e) δ13CDIC - DIC. Here, ‘HT’ and ‘LT’ indicate high and low tides, respectively.

749 750

Fig.6: Variabilities of (a) DOC - salinity, (c) DOC - pCO2, and (c) DOC - POC. Here, ‘HT’

751

and ‘LT’ indicate high and low tides, respectively.

752

753 754

Fig.7: Variabilities of (a) pCO2 - salinity, and (b) [CO2*]excess - AOU during low tide. Here,

755

‘HT’ and ‘LT’ indicate high and low tides, respectively.

Highlights •

Quantitative investigation of the effects of tidal cycle on C biogeochemistry of an estuary located in the largest mangrove ecosystem of the world.

•

DIC increased during low tide whereas DOC showed tidal influence during high tide.

•

On diurnal basis, estuaries of Indian Sundarbans acted as a source of CO2 to the regional atmosphere.

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: