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Factors controlling seasonal CO2 and CH4 emissions in three tropical mangrove-dominated estuaries in Australia
Accepted Manuscript Factors controlling seasonal CO2 and CH4 emissions in three tropical mangrovedominated estuaries in Australia Judith A. Rosentreter, D.T. Maher, D.V. Erler, R. Murray, B.D. Eyre PII:
S0272-7714(18)30568-7
DOI:
10.1016/j.ecss.2018.10.003
Reference:
YECSS 5993
To appear in:
Estuarine, Coastal and Shelf Science
Received Date: 11 July 2018 Revised Date:
3 October 2018
Accepted Date: 8 October 2018
Please cite this article as: Rosentreter, J.A., Maher, D.T., Erler, D.V., Murray, R., Eyre, B.D., Factors controlling seasonal CO2 and CH4 emissions in three tropical mangrove-dominated estuaries in Australia, Estuarine, Coastal and Shelf Science (2018), doi: https://doi.org/10.1016/j.ecss.2018.10.003. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. 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.
ACCEPTED MANUSCRIPT 1
Title: Factors controlling seasonal CO2 and CH4 emissions in three tropical mangrove-
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dominated estuaries in Australia
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Authors: Judith A. Rosentreter a,*, D.T. Maher b, D.V. Erler a, R. Murray a, B.D. Eyre a
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Affiliations: a Centre for Coastal Biogeochemistry, School of Environment, Science and Engineering, Southern Cross University, Lismore, New South Wales, Australia b
Southern Cross Geoscience, Southern Cross University, Lismore, New South Wales, Australia
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corresponding author: [email protected]
Graphical abstract
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Highlights - Emissions were within or at the high end of estuaries from Australia and globally - CO2 and CH4 fluxes were higher in the wet season compared to the dry season - Factors controlling CO2 and CH4 emissions varied spatially and seasonally - The riverine contribution determined whether CO2 and CH4 were exported to the ocean - Groundwater, terrestrial and coastal carbon inputs contributed to estuary emissions
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Keywords Carbon dioxide Methane Carbon stable isotopes Groundwater Estuary Season
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ACCEPTED MANUSCRIPT Abstract
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CO2 and CH4 emissions from estuaries of the Southern Hemisphere are greatly under-
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represented in global estuary emission estimates. This study quantifies seasonal pCO2 and
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CH4 concentrations and emissions along the salinity gradient of three tropical mangrove-
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dominated estuaries in Australia. A combination of approaches (i.e. carbon stable isotopes,
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groundwater inputs, riverine contribution, freshwater flushing times) was used to assess the
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spatial and seasonal variable factors that controlled the estuary surface water CO2 and CH4
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concentrations and hence emissions. Overall, CO2 and CH4 emissions ranged from 21.6 to
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110.4 mmol m-2 d-1 and 40.3 to 1,047.1 µmol m-2 d-1, respectively, and were within or at the
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high end compared to estuaries in Australia and globally. In the Johnstone River estuary, high
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emissions were predominantly driven by groundwater and riverine carbon inputs with exports
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of CO2 and CH4 to the ocean expected in the wet season. In the Fitzroy River estuary and
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Constant Creek estuary, in situ production and terrestrial carbon inputs were likely the main
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factors controlling CO2 and CH4 emissions. The contribution of riverine CO2 may be more
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important to overall CO2 emissions than the riverine CH4 to overall CH4 emissions in
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estuaries. The relative contribution of in situ production, the exchange with adjacent coastal
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habitats (i.e. mangroves, inter-tidal flats), and terrestrial, riverine and groundwater inputs in
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the wet and in the dry season determined whether CO2 and CH4 were fully ventilated within
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the estuaries or exported to the open ocean. The revised global estimate for estuary CO2
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emission of the latitude 0 to 23.5 ˚S is 52.1 ± 16.1 mmol m-2 d-1, which is 15% higher than a
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recent estimate of this latitudinal region.
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ACCEPTED MANUSCRIPT 1. Introduction
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Estuaries are dynamic ecosystems that connect terrestrial, riverine, oceanic and atmospheric
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carbon cycles. They receive large inputs of terrestrial organic matter, dissolved organic and
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inorganic carbon from upstream rivers, groundwater discharge, and carbon inputs via coastal
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wetlands such as salt marshes and mangroves, and the ocean (Bauer et al., 2013; Cole et al.,
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2007; Cole and Caraco, 2001; Eyre et al., 2011; Lagomasino et al., 2015; Ralison et al.,
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2008). Along the land-ocean aquatic continuum, carbon (in its different forms) is
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biogeochemically processed, sequestered in sediments or exchanged with the atmosphere or
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the ocean (Chen et al., 2013; Regnier et al., 2013; Ward et al., 2017). The oxidation of
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organic matter in estuarine waters and sediments generally result in supersaturation of CO2
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and CH4, and a subsequent flux of these greenhouse gases to the atmosphere. However, CO2
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emissions from estuaries show high temporal and spatial variability, resulting in high
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uncertainties in global annual estimates (0.094 to 0.6 Pg C y-1) (Abril and Borges, 2004;
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Bauer et al., 2013; Borges et al., 2005; Cai, 2011; Chen et al., 2013; Chen and Borges, 2009;
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Laruelle et al., 2010; Regnier et al., 2013). CO2 fluxes have been studied predominantly in
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urbanised and disturbed estuaries of the Northern Hemisphere including the U.S. (e.g.
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Raymond et al. 2000; Caffrey 2004; Joesoef et al. 2015), India (e.g. Mukhopadhyay et al.
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2002; Sarma et al. 2011), China (e.g. Chen et al. 2008; Zhai and Dai 2009), and Europe (e.g.
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Frankignoulle et al. 1998; Gazeau et al. 2004; Borges et al. 2006). A recent global estimate
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further included data from Asia and the Artic, which significantly lowered the global annual
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emissions to 0.094 Pg C y-1 (Chen et al. 2013). However, there is still a great under-
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representation in global estimates of emissions from estuaries of the Southern Hemisphere,
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especially from Australia. Of the 165 estuaries in a recent review, only 13 were from the
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Southern Hemisphere and no estuaries from Australia were included in the global annual
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emission estimate (Chen et al., 2013). Similarly, the global CO2 flux estimate for estuaries
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no data from Australia.
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CH4 emissions are much lower than CO2 emissions from estuaries, however, the global
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warming potential of CH4 is 34 to 86 times greater than CO2 (based on a 100 year and 20
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year time frame, respectively), thus CH4 is an important greenhouse gas (Shindell et al.,
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2009; Stocker et al., 2013). But CH4 flux studies are scarce compared to CO2 flux studies and
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global CH4 emissions from estuaries have even larger uncertainties varying by an order of
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magnitude (0.8 to 6.6 Tg CH4 y-1) (Bange et al., 1994; Borges and Abril, 2011; Middelburg et
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al., 2002; Upstill-Goddard et al., 2000). The high-end emission estimate of 6.6 Tg CH4 yr-1
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includes CH4 sediment-atmosphere fluxes from inter-tidal areas (Borges and Abril, 2011).
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But global emission estimates of CH4 may be even larger if accounted for CH4 ebullition and
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gas flaring, which has been shown to be a significant source in marine coastal environments
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(Borges et al., 2016; Borges et al., 2018a). Although Australia has a coastline of 35,877 km
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(Commonwealth of Australia, Geoscience Australia 2018) with 974 estuaries defined by the
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National Land and Water Resource Audit (NLWRA) (Heap et al., 2001), CO2 and CH4 fluxes
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from Australian estuaries (and the Southern Hemisphere) are greatly underrepresented in
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global annual estimates (Cai, 2011; Chen et al., 2013; Laruelle et al., 2010).
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The spatial gradient of pCO2 and the seasonal variability are much higher in estuarine waters
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compared to other coastal environments and linked to high variability of organic carbon
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production, variability of degradation processes, and changing hydrological conditions
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(Borges and Abril, 2011). The mixing of estuarine surface waters with low- pCO2 shelf and
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oceanic waters, riverine derived carbon and nutrient inputs, groundwater discharge, water
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temperature, tidal pumping, and flushing times are the major factors controlling pCO2 in
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estuaries (Borges and Abril, 2011; Chen et al., 2013; Pennino et al., 2016). Of the various
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estuaries (Battin et al., 2008; Bauer et al., 2013; Dai et al., 2012). Similarly as pCO2, CH4
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concentrations in estuaries are driven by various lateral inputs and can exhibit high spatial
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and seasonal variability (Maher et al., 2015; Nirmal Rajkumar et al., 2008; Zhang et al.,
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2008). Physical and microbial processes, such as temperature and salinity gradients, water
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depth and water mixing, submarine groundwater discharge, organic matter respiration rates
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and the availability of terminal electron acceptors are factors controlling production and
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oxidation of CH4 in estuaries (Borges and Abril, 2011; Huttunen et al., 2003). Therefore, CH4
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production rates are higher in freshwater sediments than in marine sediments where sulphate-
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reducing bacteria outcompete methanogens (Bartlett et al., 1985; Kelley et al., 1990;
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Middelburg et al., 1996). As a result, CH4 production in estuaries usually decrease towards
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the ocean (Middelburg et al., 1996).
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Whether the carbon emitted from the estuary to the atmosphere derives from the estuarine
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system itself (autochthonous) or has its origin from outside the estuarine system
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(allochthonous) has implications for coastal carbon budgets. Because of the highly variable
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environmental conditions (e.g. tidal regime, river discharge) and biogeochemical processes,
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carbon cycling in estuaries is complex and it is not yet sufficiently understood how CO2 and
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CH4 exchange in estuaries is controlled. Recently, the exchange of groundwater or porewater
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with surface water has been highlighted as an important source of CO2 and CH4 in coastal
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environments (Faber et al., 2014; Maher et al., 2015; Sadat-Noori et al., 2015b). Although
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inputs may be volumetrically low, groundwater can be highly enriched in dissolved
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constituents and should therefore be considered as a driver of CO2 and CH4 concentrations in
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estuarine surface waters and hence fluxes to the atmosphere. The stable isotopic composition
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of dissolved carbon constituents has been used in previous studies to assess carbon dynamics
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2015; Miyajima et al., 2009). In particular, the combined approach of carbon stable isotopes
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of CH4 (δ13C-CH4) and CO2 (δ13C-CO2) can give important insights into production and
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consumption pathways, and isotopic pairs are distinct in marine and freshwater environments
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(Whiticar, 1999; Whiticar and Faber, 1986).
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In this study, we combine measurements of continuous pCO2, CH4 concentration, δ13C-CH4,
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δ13C-CO2, Radon (a natural tracer of groundwater) concentrations with hydrological drivers
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(e.g. freshwater flushing times, riverine contribution to overall estuary emission), dissolved
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organic and inorganic carbon components, and physico-chemical parameters (e.g. salinity
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mixing) to assess the main drivers that control CO2 and CH4 emissions in three tropical
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mangrove-fringed estuaries in Australia. Longitudinal surveys were conducted in the wet and
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in the dry season in 2014 where concentrations, stable isotopes, and physico-chemical
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parameters were measured along the salinity gradient of each estuary. We hypothesized that
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the three estuaries will be a source of CO2 and CH4 to the atmosphere and that emissions will
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decrease along a salinity gradient towards the ocean. We further hypothesized that estuary
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concentrations and emissions will be higher in the wet season due to increased groundwater
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discharge enriched in pCO2 and CH4, as well as enhanced upstream riverine inputs that fuel
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net heterotrophy within the estuaries. As a result, we expected estuary carbon exports to the
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adjacent open ocean during the rainy season.
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2. Material and methods
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2. 1. Study sites
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Transect surveys were conducted in three semi-diurnal river-dominated mangrove-lined
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estuaries in Queensland, Australia: the Johnstone River (JR) estuary (17.509 ˚S, 146.066 ˚E),
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ACCEPTED MANUSCRIPT the Fitzroy River (FR) estuary (23.523 ˚S, 150.875 ˚E), and the Constant Creek (CC) estuary
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(20.982 ˚S, 149.031 ˚E). The studied estuaries are typical of the wet and dry tropical to
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subtropical climate zone, dominated by summer floods and winter droughts. During the wet
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season and under high flow conditions, freshwater can extend to the mouth of the estuaries
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but because of low discharge and high evaporation rates during the dry season an inverse
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circulation can occur (Eyre, 1995). The conditions of the JR and FR estuaries are categorised
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as moderately modified, while the CC estuary is categorised as largely unmodified (NLWRA,
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2001).
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The Johnstone River catchment (1,674 km2) is dominated by two large river systems, the
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North Johnstone and the South Johnstone, which meet in a single estuary before discharging
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into the Coral Sea. The catchment of the JR is located in the Wet Tropics and is one of the
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wettest catchments in Australia with annual rainfalls ranging from 1,800 mm to 5,000 mm
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per year (Furnas, 2003). The JR estuary is influenced by nutrient loads and fine sediment
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transport, a sewage treatment plant (STP), and by land use being predominantly sugar cane
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plantation in the catchment (Furnas, 2003). Mangrove forest is patchy (2.72 km2) along the
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JR estuary.
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The Fitzroy River has the largest river catchment (142,733 km2), dominated by agriculture,
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predominantly grazing (82%), but also dry land cropping (7%), horticulture, and mining
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(mainly coal) (Turner et al., 2012). Four STPs in the FR catchment, treating wastewater from
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domestic and industrial sites, discharge into the Fitzroy River. Although the FR catchment is
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moderately disturbed, wetland coverage (including mangroves) is extensive along the estuary
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and mangrove forests are dense (129.35 km2). The water surface area of the FR estuary
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significantly larger (38.1 km2) than the water surface area of the JR estuary (2.6 km2) and CC
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estuary (2.3 km2).
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catchments and located in the bioregion of the Central Queensland Coast. Grazing, forestry as
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well as sugar cane cultivation are the main land uses in the CC catchment area. The CC
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estuary has a similar water surface area to the JR estuary, but mangrove coverage along the
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CC estuary is far more extensive (8.36 km2).
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186 2.2. Survey sampling
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In each estuary, two longitudinal transect surveys along the salinity gradient were conducted
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in 2014: one survey in the wet season (February/March) and one survey in the dry season
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(September/October). A small research vessel with instrumentation installed was driven from
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the outer estuary mouth to upstream freshwater regions just after the high-tide to avoid
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sampling of the same water parcel. Surface water was pumped continuously by a submerged
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bilge pump from a water depth of approximately 30 cm into a water-air gas equilibrator
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device. The air head-space of the main equilibrator was vented to a secondary equilibrator to
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minimize artificial pressure build-up and atmospheric air contamination (Pierrot et al., 2009).
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In a closed air loop, the dried gas stream (< 0.1%) (Drierite desiccant) was pumped from the
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equilibrator head-space to a Cavity-Ring-Down-Spectroscopy (CRDS) analyser (Picarro,
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G2201-i), where CO2 and CH4 concentrations (precision 210 ppb + 0.05% and 60 ppb +
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0.05% for CO2 and CH4, respectively) and carbon stable isotopes (δ13C-CO2 precision of <
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0.12‰, δ13C-CH4 precision of < 0.16‰) were measured continuously at a ~1 sec interval
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(Maher et al., 2013). The dry molar fractions of CO2 and CH4 were corrected for water vapor
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pressure (Pierrot et al., 2009), temperature and salinity dependent solubilities (Weiss, 1974).
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The carbon stable isotopes of CO2 and CH4 were converted to standard δ13C notation by the
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instrument based on the ratio of sample
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Belemnite (VPDB)
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13
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C to the standard Vienna Pee Dee
C/12C and are reported in per mille (‰). Radon (222Rn) was measured
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every 10 minutes using a radon-in-air analyser (RAD7, Durridge), which was connected by
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tubing to the equilibrator device (Santos and Eyre, 2011).
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the dry season transect surveys. Surface water salinity, temperature, pH and dissolved oxygen
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(DO) were measured in a flow-through chamber on board every 5 minutes using a calibrated
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Hydrolab water quality multiprobe (DS5X, Aqualab). Discrete DOC, DIC and alkalinity
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(data not shown) samples were collected every 1 to 2 units of salinity. Water samples for
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DOC and DIC were filtered through 0.7 µm (Whatman GF/F) into acid-rinsed pre-combusted
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glass vials containing 200 µL 85% H3PO4 and 100 µL HgCl2, respectively, and stored at 4 °C
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until return to the laboratory. DOC concentrations were determined using an Aurora 1030W
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total organic carbon analyser. DIC concentrations were measured using a Vindta 3C
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Instrument (Marianda, Germany). Alkalinity samples were filtered (0.45 µm Whatman GF/F)
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and total alkalinity was determined via gran titration using a Metrohm Titrando automatic
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titrator, pH electrode and pre-standardized 0.01 mol L-1 HCl as titrant. Wind speed data (1-
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minute average) was obtained from weather stations close by the three estuaries provided by
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the Bureau of Meteorology (BOM) (station 039083 near Rockhampton, station 033045 near
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Mackay, station 032037 near Innisfail).
Rn data was only available for
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2.3. Calculations
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2.3.1. Water to atmosphere CO2 and CH4 fluxes
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CO2 and CH4 fluxes (F) were calculated at 1-minute intervals using the equation:
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F (mmol m-2 d-1) = k
(Cwater - Cair)
(1)
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where k is the gas transfer velocity (m d-1),
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(Wanninkhof, 2014), and Cwater and Cair is the partial pressure (µatm) of a given gas in the
is the solubility coefficient of CO2 and CH4
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ACCEPTED MANUSCRIPT water and atmosphere, respectively. For atmospheric concentrations, we assumed 400 ppm
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CO2 and 1.8 ppm CH4. The accuracy of the CO2 and CH4 fluxes greatly depend upon the gas
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transfer velocity used. Because k was not determined in situ and current velocity data was not
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available, we used wind speed estuary-specific parameterizations to calculate k. The kCO2
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was determined (1) from the revised parameterization of Wanninkhof (2014) (Eq. 2), (2) the
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parameterization of Carini et al. (1996) based on a SF6 release experiment in the Park River
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estuary (Eq. 3), and (3) the estuary specific parameterization of Jiang et al. (2008) that
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extends the commonly used exponential parameterization of Raymond and Cole (2001) for
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better flux estimates at wind speeds > 6 m s-1 (Eq. 4).
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= 0.251
.
(W14)
(2)
(C96)
(3)
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(J08)
(4)
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where k is the gas transfer velocity in cm h-1 and
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of 10 m above the water surface (m s-1) (Amorocho and DeVries, 1980). k600-CH4 has been
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found to be higher than k600-CO2 because of a non-Fickian diffusion component (microbubble
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flux) that enhances the CH4 flux relative to the CO2 flux (McGinnis et al., 2015; Prairie and
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del Giorgio, 2013; Rosentreter et al., 2017). To estimate the total CH4 flux (FCH4) in our three
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estuaries we combined the diffusive flux (FD) estimate of CH4 with a non-diffusive
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microbubble flux (FMB).
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FCH4 (µmol m-2 d-1) = FD + FMB
(5)
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with
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FMB = -1.166 + 0.0028 CH4sat + 0.042 T
(6)
260 where CH4sat is the saturation of CH4 in the water column (pCH4water/ pCH4air) and
is the
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temperature in °C. The FMB used here is slightly different from the FMB model that has been
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proposed to predict the microbubble flux in mangrove tidal creeks (Rosentreter et al., 2017).
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The original model includes CH4 saturation, water temperature and current velocity, but
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because current velocity data is not available for the estuary surveys, in this study we account
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only for CH4 saturation and water temperature (R2 = 0.39, n = 72, p < 0.001).
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In estuarine systems, the distribution of pCO2, CH4 and carbon stable isotopes can be
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determined by the conservative mixing of riverine and oceanic water depending on salinity
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(Fry, 2002; Kaldy et al., 2015; Miyajima et al., 2009). Conservative mixing of a solute was
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estimated according to Fry (2002):
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CMIX = f CR + (1 – f) CO
(7)
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where CMIX is the concentration of a solute expected by the conservative mixing model, CR is
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the concentration of the riverine end-member and CO is the concentration of the oceanic end-
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member. The freshwater fraction (f) is calculated as:
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f = (SO – S)/ (SO – SR)
(8)
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where S is the measured salinity at the estuary section, and SO and SR are the salinity of the
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oceanic and riverine end-members, respectively. To account for a buffering effect of
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were estimated as a function of the conservative mixing models (CMIX) of alkalinity and DIC
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(estimated from pCO2 and alkalinity) using the CO2SYS Microsoft Excel macro version 2.1
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(Pierrot et al., 2006). Concentrations of CO2 (µmol L-1) and CH4 (nmol L-1) were calculated
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from the gas partial pressure and solubility coefficient K0 (depending on temperature and
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salinity).
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Mixing curves of the isotopic ratios of CO2 and CH4 were calculated by using concentrations
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to weight the end-member riverine (δR) and oceanic (δO) isotopic composition (Fry, 2002):
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δ
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= !" #$ δ$ + %1 − "& #' δ' (/ #*+,
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(9)
Salinity based conservative mixing models for isotopes usually result in curvilinear mixing
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(Fry, 2002). The mixing curves show an increased function if δO > δR and a decreased
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function if δO < δR.
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2.3.3. Freshwater flushing times
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The freshwater flushing time is defined as the time required to replace the existing freshwater
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accumulated in the estuary by the river discharge. Freshwater flushing times for the FR and
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for the JR were estimated using the fraction of freshwater method, where the freshwater
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replacement time is calculated by summing the daily river discharges prior to the sampling
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date until the volume of freshwater is equal the total freshwater volume in the estuary (Eyre,
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2000; Kaul and Froelich, 1984; Kennish, 1986). The total freshwater volume in each estuary
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was estimated using the QGIS ‘raster calculator’ function, where the freshwater fraction
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values were multiplied by the depth and the width of each estuary. River discharge data was
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gauging stations of the Johnstone river (112004A and 112101B) authorised by the Water
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Monitoring Information Portal of the Queensland Department of Natural Resources and
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Mines. Freshwater flushing times could not be calculated for the CC due to the absence of
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available river discharge data for the CC estuary.
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2.3.4. Contribution of riverine CO2 and CH4 to overall estuary emissions
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The relative contribution of the riverine ventilation of a gas to the overall emissions from an
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estuary was calculated as:
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Riverine contribution (%) = (FRiver/ FEstuary × 100)
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(10)
where FRiver is the riverine flux or load of a dissolved gas to the estuary calculated from the
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river discharge and riverine excess CO2 or dissolved CH4 concentration (in mol d-1), and
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FEstuary is the area-weighted estuary flux to the atmosphere of a gas (from Eq. 1) (in mol d-1).
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The riverine excess CO2 (expressed in µmol L-1) is defined as the quantity of DIC that is
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transferred as CO2 after water-atmosphere equilibration, and was calculated after Abril et al.,
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(2000):
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Riverine excess CO2 = DICIn situ − DICEquilibrium
(11)
is the DIC river end-member (µmol L-1) measured at the most upstream
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where DICIn
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freshwater section of each estuary, and DICEquilibrium is the DIC in atmospheric equilibrium
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calculated as a function of the alkalinity river end-member (unpublished) and atmospheric
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CO2 (400 ppm) using the CO2SYS Microsoft Excel macro version 2.1 (Pierrot et al., 2006). A
situ
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ventilated to the atmosphere within the estuary and the remaining contribution is derived
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from net heterotrophy of the estuary itself or another external carbon source (e.g.
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groundwater). In contrast, a riverine ventilation contribution > 100% suggests that the
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riverine contribution of CO2 or CH4 exceeds the total emissions from within the estuary and
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the remaining CO2 or CH4 is exported to the open ocean. As for the contribution of riverine
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CO2 to overall estuary emissions, the carbonate chemistry in the estuary is affected by the
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change of pH and salinity as riverine water mixes with oceanic water. By using riverine
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excess CO2 (Eq. 11) over river DIC, the shift of inorganic carbon species (towards CO2)
343
during the mixing of river and ocean water is accounted for and should give a better estimate
344
of the riverine CO2 contribution to overall estuary emissions.
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345 3. Results
347
3.1. Estuarine conditions
348
During the wet season field campaign, water temperature ranged from 24 to 30 °C in the
349
three estuaries (Australian summer), and from 21 to 28 °C during the dry season field
350
campaign (Australian winter) (Table 1). Salinity was higher in the dry season than in the wet
351
season in the three estuaries. In the FR estuary in the wet season and in the JR in the dry
352
season, surveys were conducted over a whole salinity gradient (0 to 35). During all other
353
surveys, freshwater was either flushed to the estuary mouth (JR estuary wet season) or
354
oceanic water was pushed to the upstream river regions (e.g. CC estuary dry season). Overall,
355
wind speed (U10) ranged from 0 to 10.3 m s-1 during the wet and the dry season field
356
campaigns and was slightly higher in the wet season (Table 1). Wind speed was generally
357
lower in the JR estuary compared to the JR and FR estuaries. Dissolved oxygen
358
concentrations (DO) were similar in the JR estuary (74 to 114%), CC estuary (85 to 104%)
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ACCEPTED MANUSCRIPT and FR estuary (86 to 114%) (Table 1). pH in the three estuaries ranged from 5.95 to 7.90
360
with no clear seasonal trend (Table 1). Overall DIC concentrations ranged from 134 to 4,387
361
µmol L-1 and were on average 66%, 52% and 29% higher in the dry season compared to the
362
wet season in the JR, FR, and CC estuary, respectively (Table 1). DOC concentrations were ~
363
50% higher in the wet season compared to the dry season in all three estuaries and ranged
364
from 1.2 to 9.9 mg L-1 in the FR estuary, from 0.8 to 5.5 mg L-1 in the CC estuary and were
365
lowest in the JR (0.5 to 2.3 mg L-1). A positive correlation was found between DOC and
366
pCO2 and between DOC and CH4 in the FR and in the CC estuary. However, DOC remained
367
low with increasing pCO2 or CH4 in the JR estuary (Figure 1).
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3.2. Estuarine pCO2 and CH4 concentrations
370
During the wet and dry season field campaigns, the three estuaries were supersaturated in
371
CO2 and CH4 with respect to atmospheric equilibrium concentrations (Table 1, Figure 2).
372
Overall, pCO2 ranged from 409 to 2,924 µatm and dissolved CH4 concentrations ranged from
373
3.8 to 529.7 nmol L-1. Both, pCO2 and CH4 concentrations were higher in the JR estuary
374
compared to the FR and CC estuaries. During all surveys and in both seasons, pCO2 and CH4
375
concentrations increased from the estuary mouth to the upstream riverine sections and were
376
generally higher in the wet season compared to the dry season (Figure 2 and 3). An exception
377
was the pCO2 in the CC estuary. In the dry season, an unknown source caused an increase of
378
pCO2 at the estuary mouth. The longitudinal distribution of CH4 along the salinity gradient
379
was lower than predicted by the conservative mixing of riverine and oceanic end-members,
380
hence a loss (or sink) of CH4 along the three estuaries (Figure 3). The longitudinal
381
distribution of pCO2 in the three estuaries was less distinctive. In the JR estuary, pCO2
382
followed conservative mixing in the dry season but showed a sink of pCO2 during the wet
383
season. In the CC estuary, there was a source of CO2 along most of the estuary, in both
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seasons. In the FR estuary, pCO2 followed conservative mixing in the upper estuary and
385
changed to a source (wet season) or sink (dry season) in the lower estuary.
386 3.3. Carbon stable isotopic composition of CO2 and CH4
388
Overall, δ13C-CO2 values ranged from -18.67 to -8.84 ‰, and δ13C-CH4 values ranged from -
389
70.01 to -37.45 ‰ (Table 1). The oceanic end-member δ13C-CO2 was relatively enriched
390
compared to riverine δ13C-CO2 in the three estuaries, hence the mixing curves show an
391
increased trend (Figure 4). δ13C-CO2 versus salinity suggests conservative behaviour in the
392
dry season and non-conservative behaviour with less negative values in the wet season. An
393
exception was the JR in the dry season, where δ13C-CO2 values showed high variation along
394
the salinity gradient. In the FR dry season, a notable peak scattered around the oceanic end-
395
member was found with distinct depleted δ13C-CO2 values. δ13C-CH4 mixing showed more
396
variability along the salinity gradient between the estuaries and seasons with reference to the
397
relative enrichment or depletion of the two end-members. The isotopic ratio of CH4 was
398
however generally depleted compared to the oceanic and riverine end-members. An
399
exception was the JR in the wet season, where δ13C-CH4 was relatively enriched compared to
400
the conservative mixing curve.
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3.4. Water to atmosphere CO2 and CH4 fluxes
403
Generally, the empirical models of C96 and J08 showed good agreement (Table 2). The W14
404
model always estimated a lower CO2 or CH4 flux compared to C96 and J08 but with a
405
discrepancy of < 50%, therefore fluxes are presented as an average of the three empirical
406
models (Table 2). Overall, average wet and dry season CO2 fluxes were similar in the JR
407
estuary (75.3 ± 5.2 mmol m-2 d-1) and in the FR estuary (70.0 ± 6.7 mmol m-2 d-1), and were
408
approximately 50% lower in the CC estuary (36.1 ± 5.0 mmol m-2 d-1). Average wet and dry
16
ACCEPTED MANUSCRIPT season CH4 fluxes were also highest in the JR estuary (779.3 ± 44.9 µmol m-2 d-1), and lower
410
in the CC estuary (118.8 ± 27.8 µmol m-2 d-1) and FR estuary (99.2 ± 7.1 µmol m-2 d-1). The
411
microbubble flux (FMB) contributed more to total CH4 fluxes (FCH4) in the wet season
412
compared to the dry season in the three estuaries. In the FR in the dry season, the estimated
413
microbubble flux showed slightly negative values due to the lower CH4 saturation and
414
temperature, hence was insignificant or absent in the FR dry season (Table 2). Average CO2
415
and CH4 fluxes were approximately 50% higher in the wet season compared to the dry season
416
in the three estuaries. An exception was the CO2 flux in the CC estuary, where an inverse
417
trend was found with an average CO2 flux approximately 60% higher in the dry season
418
compared to the wet season, which was related to the increased pCO2 at the CC estuary
419
mouth in the dry season (Figure 2).
420
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3.5. Groundwater observations
422
Radon concentrations were only available for the dry season and ranged from 1,198 to 24,661
423
dpm m-3 in the JR estuary, from 476 to 3,910 dpm m-3 in the FR estuary, and from 2,803 to
424
4,230 dpm m-3 in the CC estuary (Figure 5). Because 222Rn was measured every 10 minutes,
425
only three
426
estuary is excluded from the graphical illustration in Figure 5. An inverse trend was found
427
between
428
towards lower salinities in the JR and FR (Figure 5), and likely in the CC estuary. In the JR
429
estuary, a positive relationship was found between
430
0.001) and between
222
431
relationship between
222
432
pronounced (pCO2: R2 = 0.24, n = 44, p < 0.001; CH4: R2 = 0.29, n = 44, p < 0.001) and
433
elevated pCO2 was observed around low 222Rn concentrations (Figure 5).
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Rn measurements were available for the CC estuary, therefore
Rn concentration and salinity, showing generally higher
222
222
Rn in the CC
222
Rn concentrations
Rn and pCO2 (R2 = 0.60, n = 29, p <
Rn and CH4 (R2 = 0.89, n = 29, p < 0.001). In the FR estuary, the Rn and pCO2 and between
222
Rn and CH4 was also positive but less
17
ACCEPTED MANUSCRIPT 434 3.6. Flushing times and the contribution of riverine ventilation to total emissions
436
The freshwater flushing and the tidal currents greatly influence the freshwater fractions in
437
each estuary and season. The tidal amplitude was low (2.1 m) in the JR and approximately
438
4.0 m in the FR and CC estuaries. The daily river discharge was significantly higher during
439
the surveys of the wet season (FR: 6,356 ML d-1; JR: 10,863 ML d-1) compared to the surveys
440
of the dry season (FR:139 ML d-1; JR: and 2,192 ML d-1). The freshwater flushing time in the
441
FR was 72.8 days in the dry season and 5.7 days in the wet season. In the JR estuary, the
442
flushing times were significantly shorter with 2.3 days in the dry season and 0.6 days in the
443
wet season. The riverine contribution was < 100% in all cases except the JR wet survey,
444
indicating that overall emissions of CO2 (JR dry: 38.1%; FR wet: 12.9%; FR dry: 1.5%) and
445
CH4 (JR dry: 52.9%; FR wet: 5.4%; FR dry: 0.9%) were partially related to processes within
446
the estuary or groundwater inputs rather than from riverine ventilation. In the JR estuary in
447
the wet season, the contribution of riverine ventilation of CO2 (311.0%) and CH4 (174.7%)
448
exceeded 100% suggesting that the remaining CO2 and CH4 was exported to the coastal
449
ocean (Figure 6). The contributions of riverine CO2 and CH4 to total estuarine emissions in
450
the three estuaries were higher in the wet season compared to the dry season (Figure 6).
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4. Discussion
453
4.1. Comparison of seasonal CO2 and CH4 emissions with global and other Australian
454
estuaries
455
The three mangrove-dominated estuaries in tropical Queensland have distinct differences in
456
catchment size, hydrology and geomorphology, thus cover a large range of estuarine and
457
coastal settings. The supersaturated levels in the surface water and the water to atmosphere
458
fluxes showed that the three estuaries were a source of CO2 and CH4 to the atmosphere
18
ACCEPTED MANUSCRIPT during the wet and dry season field campaigns. CO2 emissions from the JR, FR, and CC
460
estuaries were within the range or towards the upper end of global average CO2 emissions
461
from estuaries (7.74 to 35.71 mol m-2 y-1; Abril and Borges, 2005; Borges, 2005; Borges et
462
al., 2005; Cai, 2011; Chen et al., 2013, 2012; Chen and Borges, 2009; Laruelle et al., 2010)
463
(Table 3). Emission of CO2 in the CC estuary were similar to the average CO2 emission
464
proposed for subtropical and tropical estuaries (16.8 mol m-2 y-1; Borges et al., 2005),
465
whereas the JR and the FR estuaries showed slightly higher emissions (Table 3). Similar to
466
CO2, CH4 emissions from the FR and CC estuaries were also within the range of global
467
estuary emissions, whereas the emissions from the JR estuary were at the high end of global
468
estimates (Bange et al., 1994; Borges and Abril, 2011; Middelburg et al., 2002; Upstill-
469
Goddard et al., 2000). An overall average of ~ 200 mmol m-2 yr-1 from the three mangrove-
470
dominated estuaries in Queensland fits well with the higher estimate of 266 mmol m-2 y-1 for
471
all estuarine types suggested by Borges and Abril (2011).
472
A comparison of estuary CO2 emissions over latitudinal regions showed CO2 emissions can
473
vary significantly (Chen et al., 2013). Estuaries between the latitudes 23.5 and 50 °N have
474
higher CO2 emissions (63.3 ± 100.7 mmol m-2 d-1) compared to low latitudinal regions (0 to
475
23.5 °S: 44.1 ± 29.3 mmol m-2 d-1; 0 to 23.5 °N: 38.8 ± 55.4 mmol m-2 d-1), and are the lowest
476
at latitudes > 50 °N and °S (Chen et al., 2013). Including the three tropical mangrove-
477
dominated estuaries from this study, the revised global estimate for the latitudinal region 0 to
478
23.5 °S is 52.1 ± 16.1 mmol m-2 d-1, which is an increase of 15% compared to the estimate of
479
Chen et al. (2013). No such latitudinal estimates are available for estuary CH4 emissions and
480
combined CH4 emissions of estuaries, lakes, oceans, streams and wetlands did not show any
481
significant trends across latitudes and climatic zones (Ortiz-Llorente and Alvarez-Cobelas,
482
2012). However, CH4 emissions from sediments and waters in coastal mangrove tidal creeks
483
showed increased emissions at mid latitudes between 20 and 25 °N and °S, which is similar
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ACCEPTED MANUSCRIPT to the latitudinal area of the three studied estuaries here (17.5 to 23.5 °N and °S) (Rosentreter
485
et al., 2018b).
486
Since these global estimates of estuary CO2 and CH4 emissions, a number of new studies
487
have been published from the eastern coast of Australia (Table 3). The CO2 and CH4
488
emissions from the JR, FR and CC estuaries lay within the range or at the top end for
489
Australian estuaries. The degree of disturbance and stress factors in the river catchment
490
influences overall emissions of an estuary, because increased riverine and terrestrial organic
491
carbon inputs fuel net heterotrophy in the estuary zone. The large range of CO2 (-11.2 to
492
869.4 mmol m-2 d-1) and CH4 (7 to 25,800 µmol m-2 d-1) emissions between estuarine systems
493
in Australia can be attributed to the various features that characterise these estuaries. For
494
example, in the highly urbanised Sydney Harbour estuary, the CO2 efflux to the atmosphere
495
ranged from 1.2 to 5 mmol m-2 d-1 (Tanner et al., 2017) and in the urbanised Brisbane estuary
496
CH4 emissions ranged from 136 to 2,603 µmol m-2 d-1 (Sturm et al., 2017, 2016). In contrast,
497
three relatively undisturbed seagrass-dominated estuaries in Australia were net autotrophic
498
and a sink for atmospheric CO2 (-3 to -11.2 mmol m-2 d-1; Maher and Eyre, 2012). In
499
estuaries, net autotrophy is mainly related to aquatic submerged vegetation and water surface
500
area, and has been mostly observed in shallow estuaries (Caffrey, 2004; Eyre et al., 2011;
501
Ferguson and Eyre, 2010; Maher and Eyre, 2012; Santos et al., 2004). Exceptional high
502
emissions of CO2 (and CH4) in Australia were found in estuarine systems adjacent to
503
modified acidic floodplain wetlands (Ruiz-Halpern et al., 2015) or estuaries with a significant
504
contribution of groundwater inputs (Atkins et al., 2013; Sadat-Noori et al., 2015a). Korogoro
505
Creek, for example, is a surface expression of a wetland groundwater table (Sadat-Noori et
506
al., 2015a) and the North Creek study was conducted near headwaters (Atkins et al., 2013),
507
thus groundwater inputs were elevated at these study locations. The relatively high emissions
508
from the three mangrove dominated JR, FR an CC estuaries are likely controlled by a
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ACCEPTED MANUSCRIPT 509
combination of factors, which appear to shift along different parts of the estuary along the
510
salinity gradient and between seasons, and will be discussed separately for CO2 and CH4 in
511
the following sections.
512 Seasonal variability of carbon components was prominent in the mangrove-dominated
514
estuaries. CO2 and CH4 emissions were higher in the wet season compared to the dry season
515
in the JR and FR estuaries and driven by higher wind speeds and higher surface water gas
516
concentrations in the wet season. In contrast, surface water pCO2 and CO2 emissions in the
517
CC estuary were lower in the wet season than in the dry season (Figure 2). The increased
518
pCO2 in the CC in the dry season was likely derived from organic matter decomposition on
519
the extensive inter-tidal mud flats, which are found at the outer estuary mouth. This was the
520
only location where pCO2 and CO2 emissions were found elevated at the downstream transect
521
of the estuary surveys (Figure 2). DIC showed an opposite trend with significantly higher
522
concentration in the dry season in the three estuaries. High dry season DIC values were also
523
found in the Pearl River estuary in China and related to a dilution effect during the wet
524
season due to higher river discharge (Guo et al., 2008). The shifting between two mixing
525
regimes and the variation of end-member DIC (and alkalinity) between the dry and wet
526
season were responsible for complex inorganic carbon patterns in the estuarine waters. DOC
527
concentrations were higher in the wet season in the three estuaries, indicating higher
528
terrestrial carbon inputs most likely due to enhanced surface runoff in the rainy season
529
(Figure 1). Similarly, the contribution of riverine CO2 and CH4 to total emissions was higher
530
in the wet season. Distinct seasonal differences of CO2 and CH4 emissions can be of
531
importance for annual estimates. For example, CO2 and CH4 in the JR estuary was fully
532
ventilated within the estuary in the dry season but exported to the ocean in the wet season
533
(Figure 6).
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ACCEPTED MANUSCRIPT 534 4.2. Factors controlling estuarine CO2 emissions
536
In estuaries, CO2 cycling is more complex than in headwater streams and rivers because of
537
the various lateral inputs from rivers, groundwater and surface runoff, as well as in situ
538
production and the exchange with the atmosphere and the adjacent coastal ocean. In the dry
539
season, the relationship between pCO2/δ13C-CO2 and salinity suggests that mixing of
540
freshwater rich in CO2 and oceanic water rich in DIC and alkalinity was an important driver
541
of the distribution of pCO2 along the three estuaries (Figure 3 and 4). In the wet season,
542
however, sources and sinks of pCO2 and the stable isotopic ratio were more variable along
543
the estuarine salinity gradients, which highlights the different controls on CO2 cycling
544
between seasons. The positive relationship between
545
(Figure 5) further suggests that high surface water pCO2 in the upper estuaries was likely
546
driven by CO2 enriched groundwater inputs, although another co-varying factor such as
547
mixing cannot be excluded. Both, 222Rn and pCO2 increased with decreasing salinity towards
548
upstream riverine freshwater sections (Figure 3 and 5). The relationship between
549
pCO2 was more pronounced in the JR estuary (R2 = 0.60, p < 0.001) than in the FR estuary
550
(R2 = 0.24, p < 0.001). The elevated pCO2 at low
551
peaking around mid-salinities suggests that groundwater inputs were relatively low in the
552
upper FR estuary (where pCO2 was high) and inputs were higher in the mid-estuary (Figure
553
5). Although 222Rn was only available for the dry season in this study we expect an enhanced
554
contribution of groundwater inputs in the wet season in the three estuaries (Sadat-Noori et al.,
555
2015b).
556
Freshwater CO2 in this study showed depleted δ13C values around ~ -17 ‰, which reflects
557
the isotopic effect of the terrestrial carbon cycle, whereas the marine CO2 was more
558
distributed around a mean of ~ -10 ‰ (Table 1, Figure 4). The fairly abrupt change and
222
222
Rn (groundwater tracer) and pCO2
222
Rn and
Rn concentrations along with
222
Rn
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ACCEPTED MANUSCRIPT distinct depletion of δ13C-CO2 values scattered around the end-member in the FR dry season
560
may be indicative of mixing with other carbon sources i.e. benthic macroalgae (-23.1 to -16.4
561
‰), marine phytoplankton (-22.0 to -20.0 ‰), or a mangrove-derived carbon source (-35 to -
562
25 ‰) (Bouillon et al., 2008, 2007). Indeed, pCO2 and CO2 emissions from mangrove tidal
563
creeks in the JR and FR estuaries were significantly higher than from the adjacent main
564
estuary channel (64.4 to 205.2 mmol m-2 d-1; Rosentreter et al., 2018a) and tidal exports of
565
mangrove waters enriched in inorganic carbon components were likely a carbon source to the
566
main estuaries. However, non-conservative changes in δ13C-CO2 may also be related to
567
equilibrium and kinetic isotope fractionation i.e. dehydration and degassing of CO2 into the
568
atmosphere (Marlier and O’Leary, 1984; Miyajima et al., 2009; Zhang et al., 1995). Other
569
naturally occurring processes associated with kinetic fractionation, such as abiotic or
570
biogenic precipitation of CaCO3 (Romanek et al., 1992; Turner, 1982), or photosynthetic CO2
571
fixation into organic matter (Descolas-Gros and Fontugne, 1990), may also be responsible for
572
a relative enrichment of δ13C-CO2 compared to conservative mixing.
573
DOC and pCO2 have been found to have a consistent positive relationship in several
574
temperate and tropical tidal rivers and can be indicative of terrestrial organic matter inputs or
575
lateral inputs from surface runoff driving net heterotrophy and CO2 production (Borges and
576
Abril, 2011). While a strong positive relationship between DOC and pCO2 suggests a
577
connection between terrestrial organic carbon and surface water pCO2 in the FR and CC
578
estuaries, terrestrial OM inputs were not an important factor controlling CO2 emissions in the
579
JR estuary (Figure 1). In fact, the contribution of riverine CO2 to overall CO2 emissions was
580
higher in the JR estuary compared to the FR estuary. This is likely related to the short
581
residence time, which enhances the relative importance of riverine CO2 to total emissions.
582
The particular short freshwater flushing times in the JR estuary in the wet season (0.6 days),
583
freshwater flushing to the estuary mouth (salinity ~12) in combination with the high
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585
adjacent ocean. The difference of riverine excess CO2 and the emitted CO2 within the estuary
586
is 6.13 × 105 mol d-1, or in other words, 32% of the riverine CO2 was lost via gas exchange
587
within the estuary and the remaining 68% were likely exported to the ocean. In contrast,
588
flushing times in the FR estuary were long, particularly in the dry season (72.8 days), and
589
CO2 derived from the upstream river was fully ventilated within the estuary. The three
590
tropical estuaries are characterised by episodic and large freshwater inputs during the wet
591
season and low or no discharge and high evaporation rates during the dry season. Therefore,
592
the contribution of riverine CO2 to overall emissions was distinct in the wet and dry season
593
but within the range of nine other European and two U.S. estuaries (Figure 6). Borges and
594
Abril (2011) proposed that the contribution of riverine CO2 to total estuary emissions is about
595
10%, and the remaining 90% of the estuary emissions may be attributed to net heterotrophy.
596
Similarly, an average riverine contribution of 18% (range 2 to 38%) was found for the FR
597
estuary and the JR estuary in the dry season. We attribute the remaining contribution to a
598
combination of in situ production within the estuary, groundwater discharge enriched in CO2,
599
and tidal export from adjacent coastal ecosystems. The exceptional high contribution of
600
riverine CO2 in the JR in the wet season is similar to that of the Rhine in Europe with similar
601
short residence times of 1 to 3 days, which implies that most of the organic matter was
602
flushed to the estuary mouth before it could be mineralized within the estuary. Unfortunately,
603
flushing times and riverine contributions of CO2 could not be estimated for the CC estuary
604
because of the lack of river discharge data. However, we expect relatively short freshwater
605
flushing times < 5 days because of the smaller catchment size relative to surface area in the
606
CC estuary and moderate exports of CO2 to the ocean in the wet season.
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607 608
4.3. Factors controlling estuarine CH4 emissions
24
ACCEPTED MANUSCRIPT The downstream decrease of CH4 concentrations along the salinity gradient found in the JR,
610
CC and FR (Figure 3) is typical for estuaries and related to the loss of riverine CH4 due to
611
estuary emissions, microbial oxidation, and the mixing of riverine water with oceanic water
612
low in CH4 (Borges and Abril, 2011; Borges et al., 2018b; Rhee et al., 2009; Upstill-Goddard
613
and Barnes, 2016). With regard to estuary emissions, there are several pathways for CH4 to
614
reach the atmosphere from the sediment and the water column. The dominant process -
615
passive diffusion- occurs at the sediment-water and water-atmosphere interface. However,
616
there are also several non-diffusion processes. Firstly, a microbubble flux across the water-
617
atmosphere interface induced by microbubble entrainment of surface waters or formed in situ
618
under surface films or on suspended particles in supersaturated environments has been
619
highlighted recently (Beaulieu et al., 2012; McGinnis et al., 2015; Prairie and del Giorgio,
620
2013; Rosentreter et al., 2017; Woolf et al., 2007). The microbubble flux has been proposed
621
to explain an enhanced gas transfer velocity of CH4 relative to CO2 in mangrove dominated
622
estuaries (Rosentreter et al., 2017) and an increased transfer velocity up to 2.5-fold in lakes
623
(McGinnis et al., 2015; Prairie and del Giorgio, 2013). The total CH4 emissions in the JR, FR
624
and CC estuaries account for the contribution of a microbubble flux, but the microbubble flux
625
may still be underestimated as we could not include current velocity as a factor in the
626
equation (Eq.6, Table 2). An enhanced microbubble flux contribution in the wet season in the
627
three estuaries can be explained by the higher CH4 surface water concentrations, higher wind
628
speeds and increased water temperature (Australian summer). Furthermore, ebullition (rising
629
gas bubbles from sediments), active or passive plant-mediated transport, and the process of
630
tidal pumping can be important pathways of CH4 to reach the atmosphere in estuaries (Barber
631
et al., 1988; Kelley et al., 1995, 1990; Maher et al., 2015; Purvaja et al., 2004). These
632
pathways were not determined in this study and total CH4 emissions must be seen as a lower
633
limit.
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ACCEPTED MANUSCRIPT There was a positive correlation between pCO2 and CH4 in all three estuaries, suggesting a
635
common source of the two gases (Figure 7). For similar pCO2, the CH4 concentrations were,
636
however, higher in the JR estuary compared to the FR estuary and the CC estuary in the dry
637
season. STPs can be found in both, the JR and the FR catchments but the STP in the JR is
638
geographically much closer to the estuarine section surveyed, thus sewage discharge may
639
have also contributed to the increase of CH4 concentrations (and pCO2) in the JR estuary. The
640
strong relationship between
641
groundwater inputs highly enriched in CH4. Diffusive CH4 fluxes in the upper section in three
642
surveys in the North Creek estuary were also driven by CH4 enriched groundwater, either
643
directly or indirectly (Maher et al. 2015). But as mentioned above, co-variance with mixing
644
cannot be excluded. The relationship between DOC and CH4 concentrations was weak in the
645
JR estuary, but similarly to the relationship between DOC and pCO2, stronger in the FR and
646
CC estuaries, suggesting that CH4 concentration in the surface water of these estuaries was
647
also driven by terrestrial carbon inputs (Figure 1).
648
The isotopic ratio of CH4 is different for freshwater and marine environments. A rough
649
boundary around -60 ‰ can be drawn, with a mean of -59 ‰ for biogenic CH4 in freshwater
650
and a mean of -68 ‰ for marine sedimentary environments (Whiticar et al., 1986). Co-
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existing CO2-CH4 carbon stable isotope pairs indicate methane production was derived from
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hydrogenotrophic or acetoclastic methanogenesis, with a shift towards methane oxidation in
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the wet season (Figure 7). Methanogenesis by carbonate reduction has a larger CO2-CH4
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isotope separation (saline or marine region), whereas acetoclastic methanogenesis (methyl-
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type fermentation) or CH4 consumption have a smaller isotope separation, hence lower
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carbon fractionation factor values (freshwater region) (Whiticar, 1999). Indeed, a clear
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separation of isotope pairs was found between the two seasons in the JR estuary. While in the
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dry season, carbonate reduction indicative of a more saline/marine environment was the
Rn and CH4 concentrations in the JR estuary suggests
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environment was the dominant process in the wet season. The same seasonal separation
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although less pronounced was found in the FR and CC estuaries. However, without further
662
evidence from hydrogen isotopes (δD-H2O, δD-CH4&, this result must be taken with caution
663
because of the isotopic fractionation during diffusion (kinetic, equilibrium fractionation),
664
advection, transport, and mixing with other carbon sources (Whiticar and Schaefer, 2007;
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Whiticar et al., 1986).
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The riverine contribution of CH4 to overall CH4 emissions was generally less pronounced
667
than the riverine contribution of CO2 to total CO2 emissions in the JR and FR estuary (Figure
668
6). In the dry season in the JR estuary and in both seasons in the FR estuary, riverine CH4
669
was fully ventilated within the estuary, suggesting that the remaining 80% (range 47 to 99%)
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of the total emissions were driven by in situ processes within the estuary, and/or lateral
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groundwater inputs. High CH4 concentrations and emissions were found in adjacent tidal
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mangrove creeks in the JR and FR estuaries (average CH4 flux ranged from 96.5 to 1,049.8
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µmol m-2 d-1; Rosentreter et al., 2018b) suggesting tidal exports from mangrove creeks to the
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estuary main channel may have further contributed to overall emissions in the estuaries. Only
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in the wet season in the JR estuary, an export of riverine CH4 to the open ocean is expected.
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A comparison of the excess riverine CH4 and the emitted CH4 within the JR estuary suggests
677
that 57% of the riverine CH4 was lost via gas exchange in the estuary, and the remaining 43%
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(or 2.06 × 103 mol d-1 CH4) was exported to the adjacent ocean. The relative enriched δ13C-
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CH4 values compared to the conservative mixing support the hypothesis of enhanced riverine
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CH4 contribution in the rainy season in the JR, as these values indicate a more riverine origin
681
(Figure 4 and 7). Furthermore, the salinity of the oceanic end-member at the estuary mouth
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was relatively fresh (~ 12), which also indicates a strong freshwater source from upstream.
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This is the first time that the riverine CH4 contributions to overall CH4 emissions are
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estimated for estuaries and it remains to be established if the lower contribution of CH4
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compared to riverine CO2 contribution to overall emissions is a general pattern.
686 5. Conclusion
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The three tropical mangrove-fringed estuaries at the north-eastern coast of Queensland were
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supersaturated in CO2 and CH4 with respect to the atmosphere. Emissions were higher in the
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wet season compared to the dry season and within or at the upper end of the range for
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estuaries in Australia and globally. Factors controlling the CO2 and CH4 emissions varied
692
spatially and seasonally. Groundwater inputs and riverine carbon inputs were likely the main
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factors controlling CO2 and CH4 emissions in the JR estuary, while in situ production and
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terrestrial carbon inputs were the more important drivers of emissions in the FR and CC
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estuaries. The exchange with adjacent coastal tidal ecosystems (mangroves, inter-tidal flats)
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likely contributed to overall CO2 and CH4 emissions in all three estuaries. The estimation of
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the percent contribution of riverine ventilation to overall estuary emissions suggests that the
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riverine contribution is more important for estuarine CO2 than CH4. The seasonal and inter-
699
site variability of CO2 and CH4 emissions as well as the various carbon sources controlling
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the emissions from the three mangrove-dominated estuaries emphasises the need for further
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studies on carbon cycling in estuaries in Australia, and globally. This will help to better
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predict the amount of CO2 and CH4 that is ventilated within the estuary and/or exported to the
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open ocean – a prediction of great importance for the coastal global ocean under future
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climate change scenarios.
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6. Acknowledgments
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We thank Mitchell Call and Ashly McMahon for their assistance in the field. This project
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was funded by the Great Barrier Reef Foundation’s Resilient Coral Reefs Successfully
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Adapting to Climate Change research and development program in collaboration with the
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Australian Government, and by Australian Research Council Grants DE150100581,
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DP160100248, and LP150100519.
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Table 1 Average (range) of temperature, salinity, pH, DO, wind speed (U10), DOC, DIC, pCO2 and CH4 concentration and stable isotopes in the three estuaries. Salinity
pH
LDO (%)
U10 (m s-1)
DOC (mg L-1)
DIC (µmol L-1)
pCO2 (µatm)
δ13C-CO2 (‰)
CH4 (nmol L-1)
δ13C-CH4 (‰)
25.0 (24.2 - 25.8)
0.9 (0.1 - 12.3)
6.28 (5.95 - 6.99)
81 (74 - 89)
3.8 (0 - 6.1)
1.8 (1.5 - 2.3)
348 (134 - 1,025)
2,275 (502 - 2,924)
-15.77 (-16.88 - -11.66)
420.4 (185.4 - 529.7)
-47.72 (-49.92 - -46.06)
27.4 (26.2 - 28.3)
14.1 (0.03 - 34.4)
7.27 (6.69 - 7.70)
98 (93 - 114)
3.1 (0 - 5.8)
0.6 (0.5 - 1.3)
1,038 (361 - 1,982)
1,113 (409 - 2,880)
-15.00 (-17.34 - -9.95)
179.0 (3.8 - 507.8)
-50.67 (-62.52 - -45.96)
26.8 (26.2 - 27.9)
27.8 (11.6 - 35.0)
7.10 (6.80 - 7.90)
90 (85 - 99)
4.7 (3.1 - 6.1)
25.7 (25.4 - 25.9)
33.1 (30.7 - 34.4)
7.32 (7.07 - 7.51)
98 (89 - 104)
6.3 (4.7 - 7.2)
12.9 (0.2 - 28.8)
7.63 (7.36 - 7.84)
92 (86 - 97)
29.8 (21.6 - 34.6)
7.04 (6.79 - 7.28)
99 (93 - 114)
JR wet
CC wet
FR wet 28.0 (26.9 - 30.1)
980
704 (449 - 1,216)
-11.10 (-15.86 - -8.84)
52.8 (9.6 - 459.0)
-61.96 (-70.01 - -49.43)
1.5 (0.8 - 3.7)
2,870 (2,426 - 3,287)
942 (590 - 1,632)
-12.04 (-15.33 - -9.21)
26.2 (6.5 - 95.4)
-58.74 (-61.54 - -52.84)
6.3 (2.9 - 9.9)
4.7 (1.4 - 8.3)
2.6 (1.2 - 4.0)
1,842 (576 - 4,387)
2,305 (2,230 - 2,349)
1,095 (618 - 2,505)
1,139 (710 - 1,672)
-13.29 (-18.67 - -9.67)
-13.29 (-17.28 - -10.75)
27.5 (12.9 - 50.0)
25.6 (3.3 - 96.5)
-52.76 (-57.85 - -37.45)
-54.78 (-61.23 - -50.05)
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21.8 (21.2 - 22.3)
2,043 (1,790 - 2,124)
7.1 (3.6 - 10.3)
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FR dry
3.1 (2.2 - 5.5)
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CC dry
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JR dry
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Table 2 Estuary CO2 and CH4 water to atmosphere fluxes (± C.I. 95%) in the wet and in the dry season. JR dry
CC wet
CC dry
Wanninkhof (2014)
70.8 ± 4.5
25.5 ± 3.3
16.1 ± 2.4
Carini et al. (1996)
136.5 ± 6.6
49.7 ± 5.7
25.0 ± 3.5
Jiang et al. (2008)
124.0 ± 6.0
45.4 ± 5.3
23.7 ± 3.4
Average
110.4 ± 5.6
40.2 ± 4.7
Wanninkhof (2014) + FMB
792.4 ± 34.3
398.0 ± 38.8
Carini et al. (1996) + FMB
1,212.7 ± 46.5
Jiang et al. (2008) + FMB
FR dry
43.1 ± 5.9
87.7 ± 11.2
31.2 ± 1.4
51.9 ± 7.0
90.4 ± 10.3
51.7 ± 2.0
56.3 ± 7.6
109.6 ± 13.5
49.3 ± 1.9
21.6 ± 3.1
50.5 ± 6.8
95.9 ± 11.6
44.1 ± 1.8
130.0 ± 29.9
65.4 ± 16.5
148.3 ± 9.7
27.4 ± 3.3
584.8 ± 55.6
180.5 ± 40.2
78.7 ± 20.0
152.4 ± 8.6
48.4 ± 5.2
1,136.3 ± 42.1
551.71 ± 52.3
173.3 ± 38.7
84.8 ± 21.1
173.8 ± 10.8
45.1 ± 4.9
Average
1,047.1 ± 40.8
511.5 ± 48.9
161.3 ± 36.3
76.3 ± 19.2
158.1 ± 9.7
40.3 ± 4.4
(Microbubble flux contribution)
(345.4 ± 11.6)
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Average CO2 flux (mmol m-2 d-1)
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FR wet
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JR wet
(39.5 ± 11.6)
(2.4 ± 2.2)
(47.9 ± 4.6)
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Average CH4 flux (µmol m-2 d-1)
(201.7 ± 17.6)
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Table 3 Comparison of CO2 and CH4 flux studies in Australian estuaries from low to high latitudes. pCO2 (µatm)
CO2 flux (mmol m-2 d-1)
CO2 flux (mol m-2 y-1)
Johnstone River Estuary
17° S
mangroves
409 - 2,924
40.2 - 110.4
15 - 40
Constant Creek Estuary
20° S
mangroves
449 - 1,632
21.6 - 50.5
8 - 18
Fitzroy River Estuary
23° S
mangroves
618 - 2,505
44.1 - 95.9
16 - 35
Shark Bay
26° S
hypersaline
350 - 420
2.0
0.7
Brisbane River Estuary
27° S
urban
Brisbane River Estuary
27° S
urban
Brisbane River Estuary
27° S
urban, 2013
Brisbane River Estuary
27° S
urban, 2014
Broadwater Estuary
27° S
urban
Caboolture River Estuary
27° S
modified, wetlands
Caboolture River Estuary
27° S
modified, wetlands
North Creek Estuary
28° S
Richmond River Estuary
29° S
Coffs Creek Estuary
CH4 flux (µmol m-2 d-1)
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CH4 flux (mmol m-2 y-1)
Reference
3.8 - 530
512 - 1,047
187 - 382
This study
6.5 - 459
76 - 161
28 - 59
This study
3.3 - 97
40 - 158
15 - 58
This study Smith and Atkinson, (1983)
48 - 687
193 - 775
70 - 283
Sturm et al., (2016)
81 - 647
136 - 578
50 - 211
Sturm et al., (2017)
119 - 908
246 - 2,603
90 - 950
Sturm et al., (2017)
31 - 578
19 - 1,744
7 - 637
Musenze et al., (2014)
2.9 - 13.7
1-5
Macklin et al., (2014)
0.1 - 0.3
0.04 - 0.1
Adiyanti et al., (2016)
37 - 278
14 - 102
Jeffrey et al., (2018b)
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28° S
373 – 7,136 501 - 11,151
799
292
500 - 12,000
19.3 - 69.7
7 - 25
acidic wetlands
380 - 1,196
252.1
92
30° S
urban
403 – 7,920
24.1 – 94.9
9 - 35
Camden Haven
31° S
seagrass
166 - 757
-3 - -8
-1.8
Maher and Eyre, (2012)
Hasting River Estuary
31° S
seagrass
210 - 1,823
-3 - -5
-0.4
Maher and Eyre, (2012)
Korogoro Creek Estuary
31° S
mangroves, groundwater
248 - 25,135
869.4
317
Wallis Lake
32° S
seagrass
142 - 791
-11.2 - 3.5
-2
Sydney Harbour Estuary
33° S
urban
173 - 5,650
1.2 - 5
0.4 - 1.8
Yarra River Estuary
37° S
salt wedge
519 – 3,395
17.5 – 39.0
6 - 14
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North Creek Estuary
342 - 5,928
agriculture, mangroves agriculture, mangroves
CH4 (nmol L-1)
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Feature
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Latitude
Estuary
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Atkins et al., (2013) 1.8 - 150
7 - 51
3 - 19
Maher et al., (2015) Ruiz-Halpern et al., (2015)
2 - 687
3-5
39 - 193
25,800
14 - 70
9,417
Jeffrey et al., (2018a)
Sadat-Noori et al., (2015a) Maher and Eyre, (2012) Tanner et al., (2017)
47 – 1,303
110 - 840
40 - 307
Tait et al., (2017)
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Figure 1 DOC concentrations versus (a) pCO2 and (b) CH4 concentrations in the JR estuary, CC estuary and FR estuary. The lines represent the linear regression lines.
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Figure 2 pCO2 and CH4 concentration gradients in the JR estuary, the CC estuary and the FR estuary. The left panel shows the wet season, the right panel shows the dry season, respectively. Average CO2 and CH4 emissions over the estuary surveys from Table 2 are presented in each graph.
1008
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Figure 3 Longitudinal distribution of pCO2 and CH4 along the salinity gradient in the JR estuary, CC estuary and FR estuary. pCO2 and CH4 concentrations lower than predicted by the conservative mixing lines (black dotted line) indicate a sink (or loss) along the salinity gradient. Concentrations above the mixing lines indicate a source of CO2 or CH4.
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Figure 4 Longitudinal distribution of δ13C-CO2 and δ13C-CH4 along the salinity gradient in the JR estuary, CC estuary and FR estuary. The conservative mixing curves (black dotted line) show an increased function if δO > δR and a decreased function if δO < δR. δ13C-CO2 and δ13C-CH4 values in the three estuaries follow conservative mixing, are depleted (below) or enriched (above) relative to the freshwater and oceanic end-members.
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Figure 5 Groundwater (222Rn) over the salinity gradient a) in the JR estuary and b) in the FR estuary, and the correlation between 222Rn and pCO2 and CH4 c) in the JR estuary and d) in the FR estuary in the dry season. The 222Rn concentrations in the CC estuary are not illustrated in this figure because only three data point were available for 222Rn.
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Figure 6 Contribution (as in %) of the riverine ventilation of a) CO2 and b) CH4 to the overall emissions in the JR estuary (dark green) and FR estuary (light green) in the wet and dry season. The percent contribution is calculated from the riverine load and the estuary areaweighted emissions (see Eq. 10). The data of the nine European estuaries and two US estuaries are derived from Borges and Abril (2011): Rhine (Rh), Randers Fjord (Ra), Loire (Lo), Elbe (El), Sado (Sad), Ems (Em), York River (YR), Thames (Th), Gironde (Gi), Satilla (Sat), and Scheldt (Sch). If the riverine contribution exceeds the total emissions from within the estuary (above 100% line), the remaining CO2 or CH4 is exported to the open ocean. The graph 6a) was adapted from Borges and Abril (2011).
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Figure 7 Comparison of a) pCO2 versus CH4 concentrations in the JR estuary, in the CC estuary and in the FR estuary in the wet and dry season, and b) δ13C-CO2 versus δ13C-CH4. The dashed lines are the carbon fractionation factor lines that indicate the proposed boundaries between hydrogenotrophic methanogenesis (saline, marine region), acetoclastic methanogenesis (freshwater region), and methane oxidation (Whiticar, 1999; Whiticar and Faber, 1986).The concentrations and δ13C data in the JR are shown for the main arm and south arm surveys.
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End of Article
48
S0272-7714(18)30568-7
DOI:
10.1016/j.ecss.2018.10.003
Reference:
YECSS 5993
To appear in:
Estuarine, Coastal and Shelf Science
Received Date: 11 July 2018 Revised Date:
3 October 2018
Accepted Date: 8 October 2018
Please cite this article as: Rosentreter, J.A., Maher, D.T., Erler, D.V., Murray, R., Eyre, B.D., Factors controlling seasonal CO2 and CH4 emissions in three tropical mangrove-dominated estuaries in Australia, Estuarine, Coastal and Shelf Science (2018), doi: https://doi.org/10.1016/j.ecss.2018.10.003. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. 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.
ACCEPTED MANUSCRIPT 1
Title: Factors controlling seasonal CO2 and CH4 emissions in three tropical mangrove-
2
dominated estuaries in Australia
3
Authors: Judith A. Rosentreter a,*, D.T. Maher b, D.V. Erler a, R. Murray a, B.D. Eyre a
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Affiliations: a Centre for Coastal Biogeochemistry, School of Environment, Science and Engineering, Southern Cross University, Lismore, New South Wales, Australia b
Southern Cross Geoscience, Southern Cross University, Lismore, New South Wales, Australia
*
corresponding author: [email protected]
Graphical abstract
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Highlights - Emissions were within or at the high end of estuaries from Australia and globally - CO2 and CH4 fluxes were higher in the wet season compared to the dry season - Factors controlling CO2 and CH4 emissions varied spatially and seasonally - The riverine contribution determined whether CO2 and CH4 were exported to the ocean - Groundwater, terrestrial and coastal carbon inputs contributed to estuary emissions
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Keywords Carbon dioxide Methane Carbon stable isotopes Groundwater Estuary Season
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1
ACCEPTED MANUSCRIPT Abstract
35
CO2 and CH4 emissions from estuaries of the Southern Hemisphere are greatly under-
36
represented in global estuary emission estimates. This study quantifies seasonal pCO2 and
37
CH4 concentrations and emissions along the salinity gradient of three tropical mangrove-
38
dominated estuaries in Australia. A combination of approaches (i.e. carbon stable isotopes,
39
groundwater inputs, riverine contribution, freshwater flushing times) was used to assess the
40
spatial and seasonal variable factors that controlled the estuary surface water CO2 and CH4
41
concentrations and hence emissions. Overall, CO2 and CH4 emissions ranged from 21.6 to
42
110.4 mmol m-2 d-1 and 40.3 to 1,047.1 µmol m-2 d-1, respectively, and were within or at the
43
high end compared to estuaries in Australia and globally. In the Johnstone River estuary, high
44
emissions were predominantly driven by groundwater and riverine carbon inputs with exports
45
of CO2 and CH4 to the ocean expected in the wet season. In the Fitzroy River estuary and
46
Constant Creek estuary, in situ production and terrestrial carbon inputs were likely the main
47
factors controlling CO2 and CH4 emissions. The contribution of riverine CO2 may be more
48
important to overall CO2 emissions than the riverine CH4 to overall CH4 emissions in
49
estuaries. The relative contribution of in situ production, the exchange with adjacent coastal
50
habitats (i.e. mangroves, inter-tidal flats), and terrestrial, riverine and groundwater inputs in
51
the wet and in the dry season determined whether CO2 and CH4 were fully ventilated within
52
the estuaries or exported to the open ocean. The revised global estimate for estuary CO2
53
emission of the latitude 0 to 23.5 ˚S is 52.1 ± 16.1 mmol m-2 d-1, which is 15% higher than a
54
recent estimate of this latitudinal region.
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ACCEPTED MANUSCRIPT 1. Introduction
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Estuaries are dynamic ecosystems that connect terrestrial, riverine, oceanic and atmospheric
59
carbon cycles. They receive large inputs of terrestrial organic matter, dissolved organic and
60
inorganic carbon from upstream rivers, groundwater discharge, and carbon inputs via coastal
61
wetlands such as salt marshes and mangroves, and the ocean (Bauer et al., 2013; Cole et al.,
62
2007; Cole and Caraco, 2001; Eyre et al., 2011; Lagomasino et al., 2015; Ralison et al.,
63
2008). Along the land-ocean aquatic continuum, carbon (in its different forms) is
64
biogeochemically processed, sequestered in sediments or exchanged with the atmosphere or
65
the ocean (Chen et al., 2013; Regnier et al., 2013; Ward et al., 2017). The oxidation of
66
organic matter in estuarine waters and sediments generally result in supersaturation of CO2
67
and CH4, and a subsequent flux of these greenhouse gases to the atmosphere. However, CO2
68
emissions from estuaries show high temporal and spatial variability, resulting in high
69
uncertainties in global annual estimates (0.094 to 0.6 Pg C y-1) (Abril and Borges, 2004;
70
Bauer et al., 2013; Borges et al., 2005; Cai, 2011; Chen et al., 2013; Chen and Borges, 2009;
71
Laruelle et al., 2010; Regnier et al., 2013). CO2 fluxes have been studied predominantly in
72
urbanised and disturbed estuaries of the Northern Hemisphere including the U.S. (e.g.
73
Raymond et al. 2000; Caffrey 2004; Joesoef et al. 2015), India (e.g. Mukhopadhyay et al.
74
2002; Sarma et al. 2011), China (e.g. Chen et al. 2008; Zhai and Dai 2009), and Europe (e.g.
75
Frankignoulle et al. 1998; Gazeau et al. 2004; Borges et al. 2006). A recent global estimate
76
further included data from Asia and the Artic, which significantly lowered the global annual
77
emissions to 0.094 Pg C y-1 (Chen et al. 2013). However, there is still a great under-
78
representation in global estimates of emissions from estuaries of the Southern Hemisphere,
79
especially from Australia. Of the 165 estuaries in a recent review, only 13 were from the
80
Southern Hemisphere and no estuaries from Australia were included in the global annual
81
emission estimate (Chen et al., 2013). Similarly, the global CO2 flux estimate for estuaries
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no data from Australia.
84
CH4 emissions are much lower than CO2 emissions from estuaries, however, the global
85
warming potential of CH4 is 34 to 86 times greater than CO2 (based on a 100 year and 20
86
year time frame, respectively), thus CH4 is an important greenhouse gas (Shindell et al.,
87
2009; Stocker et al., 2013). But CH4 flux studies are scarce compared to CO2 flux studies and
88
global CH4 emissions from estuaries have even larger uncertainties varying by an order of
89
magnitude (0.8 to 6.6 Tg CH4 y-1) (Bange et al., 1994; Borges and Abril, 2011; Middelburg et
90
al., 2002; Upstill-Goddard et al., 2000). The high-end emission estimate of 6.6 Tg CH4 yr-1
91
includes CH4 sediment-atmosphere fluxes from inter-tidal areas (Borges and Abril, 2011).
92
But global emission estimates of CH4 may be even larger if accounted for CH4 ebullition and
93
gas flaring, which has been shown to be a significant source in marine coastal environments
94
(Borges et al., 2016; Borges et al., 2018a). Although Australia has a coastline of 35,877 km
95
(Commonwealth of Australia, Geoscience Australia 2018) with 974 estuaries defined by the
96
National Land and Water Resource Audit (NLWRA) (Heap et al., 2001), CO2 and CH4 fluxes
97
from Australian estuaries (and the Southern Hemisphere) are greatly underrepresented in
98
global annual estimates (Cai, 2011; Chen et al., 2013; Laruelle et al., 2010).
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The spatial gradient of pCO2 and the seasonal variability are much higher in estuarine waters
101
compared to other coastal environments and linked to high variability of organic carbon
102
production, variability of degradation processes, and changing hydrological conditions
103
(Borges and Abril, 2011). The mixing of estuarine surface waters with low- pCO2 shelf and
104
oceanic waters, riverine derived carbon and nutrient inputs, groundwater discharge, water
105
temperature, tidal pumping, and flushing times are the major factors controlling pCO2 in
106
estuaries (Borges and Abril, 2011; Chen et al., 2013; Pennino et al., 2016). Of the various
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108
estuaries (Battin et al., 2008; Bauer et al., 2013; Dai et al., 2012). Similarly as pCO2, CH4
109
concentrations in estuaries are driven by various lateral inputs and can exhibit high spatial
110
and seasonal variability (Maher et al., 2015; Nirmal Rajkumar et al., 2008; Zhang et al.,
111
2008). Physical and microbial processes, such as temperature and salinity gradients, water
112
depth and water mixing, submarine groundwater discharge, organic matter respiration rates
113
and the availability of terminal electron acceptors are factors controlling production and
114
oxidation of CH4 in estuaries (Borges and Abril, 2011; Huttunen et al., 2003). Therefore, CH4
115
production rates are higher in freshwater sediments than in marine sediments where sulphate-
116
reducing bacteria outcompete methanogens (Bartlett et al., 1985; Kelley et al., 1990;
117
Middelburg et al., 1996). As a result, CH4 production in estuaries usually decrease towards
118
the ocean (Middelburg et al., 1996).
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Whether the carbon emitted from the estuary to the atmosphere derives from the estuarine
121
system itself (autochthonous) or has its origin from outside the estuarine system
122
(allochthonous) has implications for coastal carbon budgets. Because of the highly variable
123
environmental conditions (e.g. tidal regime, river discharge) and biogeochemical processes,
124
carbon cycling in estuaries is complex and it is not yet sufficiently understood how CO2 and
125
CH4 exchange in estuaries is controlled. Recently, the exchange of groundwater or porewater
126
with surface water has been highlighted as an important source of CO2 and CH4 in coastal
127
environments (Faber et al., 2014; Maher et al., 2015; Sadat-Noori et al., 2015b). Although
128
inputs may be volumetrically low, groundwater can be highly enriched in dissolved
129
constituents and should therefore be considered as a driver of CO2 and CH4 concentrations in
130
estuarine surface waters and hence fluxes to the atmosphere. The stable isotopic composition
131
of dissolved carbon constituents has been used in previous studies to assess carbon dynamics
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133
2015; Miyajima et al., 2009). In particular, the combined approach of carbon stable isotopes
134
of CH4 (δ13C-CH4) and CO2 (δ13C-CO2) can give important insights into production and
135
consumption pathways, and isotopic pairs are distinct in marine and freshwater environments
136
(Whiticar, 1999; Whiticar and Faber, 1986).
137
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In this study, we combine measurements of continuous pCO2, CH4 concentration, δ13C-CH4,
139
δ13C-CO2, Radon (a natural tracer of groundwater) concentrations with hydrological drivers
140
(e.g. freshwater flushing times, riverine contribution to overall estuary emission), dissolved
141
organic and inorganic carbon components, and physico-chemical parameters (e.g. salinity
142
mixing) to assess the main drivers that control CO2 and CH4 emissions in three tropical
143
mangrove-fringed estuaries in Australia. Longitudinal surveys were conducted in the wet and
144
in the dry season in 2014 where concentrations, stable isotopes, and physico-chemical
145
parameters were measured along the salinity gradient of each estuary. We hypothesized that
146
the three estuaries will be a source of CO2 and CH4 to the atmosphere and that emissions will
147
decrease along a salinity gradient towards the ocean. We further hypothesized that estuary
148
concentrations and emissions will be higher in the wet season due to increased groundwater
149
discharge enriched in pCO2 and CH4, as well as enhanced upstream riverine inputs that fuel
150
net heterotrophy within the estuaries. As a result, we expected estuary carbon exports to the
151
adjacent open ocean during the rainy season.
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2. Material and methods
154
2. 1. Study sites
155
Transect surveys were conducted in three semi-diurnal river-dominated mangrove-lined
156
estuaries in Queensland, Australia: the Johnstone River (JR) estuary (17.509 ˚S, 146.066 ˚E),
6
ACCEPTED MANUSCRIPT the Fitzroy River (FR) estuary (23.523 ˚S, 150.875 ˚E), and the Constant Creek (CC) estuary
158
(20.982 ˚S, 149.031 ˚E). The studied estuaries are typical of the wet and dry tropical to
159
subtropical climate zone, dominated by summer floods and winter droughts. During the wet
160
season and under high flow conditions, freshwater can extend to the mouth of the estuaries
161
but because of low discharge and high evaporation rates during the dry season an inverse
162
circulation can occur (Eyre, 1995). The conditions of the JR and FR estuaries are categorised
163
as moderately modified, while the CC estuary is categorised as largely unmodified (NLWRA,
164
2001).
165
The Johnstone River catchment (1,674 km2) is dominated by two large river systems, the
166
North Johnstone and the South Johnstone, which meet in a single estuary before discharging
167
into the Coral Sea. The catchment of the JR is located in the Wet Tropics and is one of the
168
wettest catchments in Australia with annual rainfalls ranging from 1,800 mm to 5,000 mm
169
per year (Furnas, 2003). The JR estuary is influenced by nutrient loads and fine sediment
170
transport, a sewage treatment plant (STP), and by land use being predominantly sugar cane
171
plantation in the catchment (Furnas, 2003). Mangrove forest is patchy (2.72 km2) along the
172
JR estuary.
173
The Fitzroy River has the largest river catchment (142,733 km2), dominated by agriculture,
174
predominantly grazing (82%), but also dry land cropping (7%), horticulture, and mining
175
(mainly coal) (Turner et al., 2012). Four STPs in the FR catchment, treating wastewater from
176
domestic and industrial sites, discharge into the Fitzroy River. Although the FR catchment is
177
moderately disturbed, wetland coverage (including mangroves) is extensive along the estuary
178
and mangrove forests are dense (129.35 km2). The water surface area of the FR estuary
179
significantly larger (38.1 km2) than the water surface area of the JR estuary (2.6 km2) and CC
180
estuary (2.3 km2).
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ACCEPTED MANUSCRIPT The Constant Creek catchment is relatively small (139 km2) compared to the other
182
catchments and located in the bioregion of the Central Queensland Coast. Grazing, forestry as
183
well as sugar cane cultivation are the main land uses in the CC catchment area. The CC
184
estuary has a similar water surface area to the JR estuary, but mangrove coverage along the
185
CC estuary is far more extensive (8.36 km2).
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186 2.2. Survey sampling
188
In each estuary, two longitudinal transect surveys along the salinity gradient were conducted
189
in 2014: one survey in the wet season (February/March) and one survey in the dry season
190
(September/October). A small research vessel with instrumentation installed was driven from
191
the outer estuary mouth to upstream freshwater regions just after the high-tide to avoid
192
sampling of the same water parcel. Surface water was pumped continuously by a submerged
193
bilge pump from a water depth of approximately 30 cm into a water-air gas equilibrator
194
device. The air head-space of the main equilibrator was vented to a secondary equilibrator to
195
minimize artificial pressure build-up and atmospheric air contamination (Pierrot et al., 2009).
196
In a closed air loop, the dried gas stream (< 0.1%) (Drierite desiccant) was pumped from the
197
equilibrator head-space to a Cavity-Ring-Down-Spectroscopy (CRDS) analyser (Picarro,
198
G2201-i), where CO2 and CH4 concentrations (precision 210 ppb + 0.05% and 60 ppb +
199
0.05% for CO2 and CH4, respectively) and carbon stable isotopes (δ13C-CO2 precision of <
200
0.12‰, δ13C-CH4 precision of < 0.16‰) were measured continuously at a ~1 sec interval
201
(Maher et al., 2013). The dry molar fractions of CO2 and CH4 were corrected for water vapor
202
pressure (Pierrot et al., 2009), temperature and salinity dependent solubilities (Weiss, 1974).
203
The carbon stable isotopes of CO2 and CH4 were converted to standard δ13C notation by the
204
instrument based on the ratio of sample
205
Belemnite (VPDB)
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13
12
C and
13
C to the standard Vienna Pee Dee
C/12C and are reported in per mille (‰). Radon (222Rn) was measured
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every 10 minutes using a radon-in-air analyser (RAD7, Durridge), which was connected by
207
tubing to the equilibrator device (Santos and Eyre, 2011).
208
the dry season transect surveys. Surface water salinity, temperature, pH and dissolved oxygen
209
(DO) were measured in a flow-through chamber on board every 5 minutes using a calibrated
210
Hydrolab water quality multiprobe (DS5X, Aqualab). Discrete DOC, DIC and alkalinity
211
(data not shown) samples were collected every 1 to 2 units of salinity. Water samples for
212
DOC and DIC were filtered through 0.7 µm (Whatman GF/F) into acid-rinsed pre-combusted
213
glass vials containing 200 µL 85% H3PO4 and 100 µL HgCl2, respectively, and stored at 4 °C
214
until return to the laboratory. DOC concentrations were determined using an Aurora 1030W
215
total organic carbon analyser. DIC concentrations were measured using a Vindta 3C
216
Instrument (Marianda, Germany). Alkalinity samples were filtered (0.45 µm Whatman GF/F)
217
and total alkalinity was determined via gran titration using a Metrohm Titrando automatic
218
titrator, pH electrode and pre-standardized 0.01 mol L-1 HCl as titrant. Wind speed data (1-
219
minute average) was obtained from weather stations close by the three estuaries provided by
220
the Bureau of Meteorology (BOM) (station 039083 near Rockhampton, station 033045 near
221
Mackay, station 032037 near Innisfail).
Rn data was only available for
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2.3. Calculations
224
2.3.1. Water to atmosphere CO2 and CH4 fluxes
225
CO2 and CH4 fluxes (F) were calculated at 1-minute intervals using the equation:
226 227
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F (mmol m-2 d-1) = k
(Cwater - Cair)
(1)
228 229
where k is the gas transfer velocity (m d-1),
230
(Wanninkhof, 2014), and Cwater and Cair is the partial pressure (µatm) of a given gas in the
is the solubility coefficient of CO2 and CH4
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232
CO2 and 1.8 ppm CH4. The accuracy of the CO2 and CH4 fluxes greatly depend upon the gas
233
transfer velocity used. Because k was not determined in situ and current velocity data was not
234
available, we used wind speed estuary-specific parameterizations to calculate k. The kCO2
235
was determined (1) from the revised parameterization of Wanninkhof (2014) (Eq. 2), (2) the
236
parameterization of Carini et al. (1996) based on a SF6 release experiment in the Park River
237
estuary (Eq. 3), and (3) the estuary specific parameterization of Jiang et al. (2008) that
238
extends the commonly used exponential parameterization of Raymond and Cole (2001) for
239
better flux estimates at wind speeds > 6 m s-1 (Eq. 4).
241
= 0.251
.
(W14)
(2)
(C96)
(3)
242 = 0.045 + 2.0277
243 244
− 0.436
+ 3.99
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= 0.314
245
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(J08)
(4)
247
where k is the gas transfer velocity in cm h-1 and
248
of 10 m above the water surface (m s-1) (Amorocho and DeVries, 1980). k600-CH4 has been
249
found to be higher than k600-CO2 because of a non-Fickian diffusion component (microbubble
250
flux) that enhances the CH4 flux relative to the CO2 flux (McGinnis et al., 2015; Prairie and
251
del Giorgio, 2013; Rosentreter et al., 2017). To estimate the total CH4 flux (FCH4) in our three
252
estuaries we combined the diffusive flux (FD) estimate of CH4 with a non-diffusive
253
microbubble flux (FMB).
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254 255
FCH4 (µmol m-2 d-1) = FD + FMB
(5)
256 257
with
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FMB = -1.166 + 0.0028 CH4sat + 0.042 T
(6)
260 where CH4sat is the saturation of CH4 in the water column (pCH4water/ pCH4air) and
is the
262
temperature in °C. The FMB used here is slightly different from the FMB model that has been
263
proposed to predict the microbubble flux in mangrove tidal creeks (Rosentreter et al., 2017).
264
The original model includes CH4 saturation, water temperature and current velocity, but
265
because current velocity data is not available for the estuary surveys, in this study we account
266
only for CH4 saturation and water temperature (R2 = 0.39, n = 72, p < 0.001).
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In estuarine systems, the distribution of pCO2, CH4 and carbon stable isotopes can be
270
determined by the conservative mixing of riverine and oceanic water depending on salinity
271
(Fry, 2002; Kaldy et al., 2015; Miyajima et al., 2009). Conservative mixing of a solute was
272
estimated according to Fry (2002):
273
275
CMIX = f CR + (1 – f) CO
(7)
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where CMIX is the concentration of a solute expected by the conservative mixing model, CR is
277
the concentration of the riverine end-member and CO is the concentration of the oceanic end-
278
member. The freshwater fraction (f) is calculated as:
279 280
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f = (SO – S)/ (SO – SR)
(8)
281 282
where S is the measured salinity at the estuary section, and SO and SR are the salinity of the
283
oceanic and riverine end-members, respectively. To account for a buffering effect of
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285
were estimated as a function of the conservative mixing models (CMIX) of alkalinity and DIC
286
(estimated from pCO2 and alkalinity) using the CO2SYS Microsoft Excel macro version 2.1
287
(Pierrot et al., 2006). Concentrations of CO2 (µmol L-1) and CH4 (nmol L-1) were calculated
288
from the gas partial pressure and solubility coefficient K0 (depending on temperature and
289
salinity).
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Mixing curves of the isotopic ratios of CO2 and CH4 were calculated by using concentrations
292
to weight the end-member riverine (δR) and oceanic (δO) isotopic composition (Fry, 2002):
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294
δ
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= !" #$ δ$ + %1 − "& #' δ' (/ #*+,
295
(9)
Salinity based conservative mixing models for isotopes usually result in curvilinear mixing
297
(Fry, 2002). The mixing curves show an increased function if δO > δR and a decreased
298
function if δO < δR.
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2.3.3. Freshwater flushing times
301
The freshwater flushing time is defined as the time required to replace the existing freshwater
302
accumulated in the estuary by the river discharge. Freshwater flushing times for the FR and
303
for the JR were estimated using the fraction of freshwater method, where the freshwater
304
replacement time is calculated by summing the daily river discharges prior to the sampling
305
date until the volume of freshwater is equal the total freshwater volume in the estuary (Eyre,
306
2000; Kaul and Froelich, 1984; Kennish, 1986). The total freshwater volume in each estuary
307
was estimated using the QGIS ‘raster calculator’ function, where the freshwater fraction
308
values were multiplied by the depth and the width of each estuary. River discharge data was
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310
gauging stations of the Johnstone river (112004A and 112101B) authorised by the Water
311
Monitoring Information Portal of the Queensland Department of Natural Resources and
312
Mines. Freshwater flushing times could not be calculated for the CC due to the absence of
313
available river discharge data for the CC estuary.
314
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2.3.4. Contribution of riverine CO2 and CH4 to overall estuary emissions
316
The relative contribution of the riverine ventilation of a gas to the overall emissions from an
317
estuary was calculated as:
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Riverine contribution (%) = (FRiver/ FEstuary × 100)
320
(10)
where FRiver is the riverine flux or load of a dissolved gas to the estuary calculated from the
322
river discharge and riverine excess CO2 or dissolved CH4 concentration (in mol d-1), and
323
FEstuary is the area-weighted estuary flux to the atmosphere of a gas (from Eq. 1) (in mol d-1).
324
The riverine excess CO2 (expressed in µmol L-1) is defined as the quantity of DIC that is
325
transferred as CO2 after water-atmosphere equilibration, and was calculated after Abril et al.,
326
(2000):
328 329
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Riverine excess CO2 = DICIn situ − DICEquilibrium
(11)
is the DIC river end-member (µmol L-1) measured at the most upstream
330
where DICIn
331
freshwater section of each estuary, and DICEquilibrium is the DIC in atmospheric equilibrium
332
calculated as a function of the alkalinity river end-member (unpublished) and atmospheric
333
CO2 (400 ppm) using the CO2SYS Microsoft Excel macro version 2.1 (Pierrot et al., 2006). A
situ
13
ACCEPTED MANUSCRIPT riverine ventilation contribution of < 100% indicates that the riverine CO2 or CH4 is fully
335
ventilated to the atmosphere within the estuary and the remaining contribution is derived
336
from net heterotrophy of the estuary itself or another external carbon source (e.g.
337
groundwater). In contrast, a riverine ventilation contribution > 100% suggests that the
338
riverine contribution of CO2 or CH4 exceeds the total emissions from within the estuary and
339
the remaining CO2 or CH4 is exported to the open ocean. As for the contribution of riverine
340
CO2 to overall estuary emissions, the carbonate chemistry in the estuary is affected by the
341
change of pH and salinity as riverine water mixes with oceanic water. By using riverine
342
excess CO2 (Eq. 11) over river DIC, the shift of inorganic carbon species (towards CO2)
343
during the mixing of river and ocean water is accounted for and should give a better estimate
344
of the riverine CO2 contribution to overall estuary emissions.
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345 3. Results
347
3.1. Estuarine conditions
348
During the wet season field campaign, water temperature ranged from 24 to 30 °C in the
349
three estuaries (Australian summer), and from 21 to 28 °C during the dry season field
350
campaign (Australian winter) (Table 1). Salinity was higher in the dry season than in the wet
351
season in the three estuaries. In the FR estuary in the wet season and in the JR in the dry
352
season, surveys were conducted over a whole salinity gradient (0 to 35). During all other
353
surveys, freshwater was either flushed to the estuary mouth (JR estuary wet season) or
354
oceanic water was pushed to the upstream river regions (e.g. CC estuary dry season). Overall,
355
wind speed (U10) ranged from 0 to 10.3 m s-1 during the wet and the dry season field
356
campaigns and was slightly higher in the wet season (Table 1). Wind speed was generally
357
lower in the JR estuary compared to the JR and FR estuaries. Dissolved oxygen
358
concentrations (DO) were similar in the JR estuary (74 to 114%), CC estuary (85 to 104%)
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360
with no clear seasonal trend (Table 1). Overall DIC concentrations ranged from 134 to 4,387
361
µmol L-1 and were on average 66%, 52% and 29% higher in the dry season compared to the
362
wet season in the JR, FR, and CC estuary, respectively (Table 1). DOC concentrations were ~
363
50% higher in the wet season compared to the dry season in all three estuaries and ranged
364
from 1.2 to 9.9 mg L-1 in the FR estuary, from 0.8 to 5.5 mg L-1 in the CC estuary and were
365
lowest in the JR (0.5 to 2.3 mg L-1). A positive correlation was found between DOC and
366
pCO2 and between DOC and CH4 in the FR and in the CC estuary. However, DOC remained
367
low with increasing pCO2 or CH4 in the JR estuary (Figure 1).
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3.2. Estuarine pCO2 and CH4 concentrations
370
During the wet and dry season field campaigns, the three estuaries were supersaturated in
371
CO2 and CH4 with respect to atmospheric equilibrium concentrations (Table 1, Figure 2).
372
Overall, pCO2 ranged from 409 to 2,924 µatm and dissolved CH4 concentrations ranged from
373
3.8 to 529.7 nmol L-1. Both, pCO2 and CH4 concentrations were higher in the JR estuary
374
compared to the FR and CC estuaries. During all surveys and in both seasons, pCO2 and CH4
375
concentrations increased from the estuary mouth to the upstream riverine sections and were
376
generally higher in the wet season compared to the dry season (Figure 2 and 3). An exception
377
was the pCO2 in the CC estuary. In the dry season, an unknown source caused an increase of
378
pCO2 at the estuary mouth. The longitudinal distribution of CH4 along the salinity gradient
379
was lower than predicted by the conservative mixing of riverine and oceanic end-members,
380
hence a loss (or sink) of CH4 along the three estuaries (Figure 3). The longitudinal
381
distribution of pCO2 in the three estuaries was less distinctive. In the JR estuary, pCO2
382
followed conservative mixing in the dry season but showed a sink of pCO2 during the wet
383
season. In the CC estuary, there was a source of CO2 along most of the estuary, in both
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seasons. In the FR estuary, pCO2 followed conservative mixing in the upper estuary and
385
changed to a source (wet season) or sink (dry season) in the lower estuary.
386 3.3. Carbon stable isotopic composition of CO2 and CH4
388
Overall, δ13C-CO2 values ranged from -18.67 to -8.84 ‰, and δ13C-CH4 values ranged from -
389
70.01 to -37.45 ‰ (Table 1). The oceanic end-member δ13C-CO2 was relatively enriched
390
compared to riverine δ13C-CO2 in the three estuaries, hence the mixing curves show an
391
increased trend (Figure 4). δ13C-CO2 versus salinity suggests conservative behaviour in the
392
dry season and non-conservative behaviour with less negative values in the wet season. An
393
exception was the JR in the dry season, where δ13C-CO2 values showed high variation along
394
the salinity gradient. In the FR dry season, a notable peak scattered around the oceanic end-
395
member was found with distinct depleted δ13C-CO2 values. δ13C-CH4 mixing showed more
396
variability along the salinity gradient between the estuaries and seasons with reference to the
397
relative enrichment or depletion of the two end-members. The isotopic ratio of CH4 was
398
however generally depleted compared to the oceanic and riverine end-members. An
399
exception was the JR in the wet season, where δ13C-CH4 was relatively enriched compared to
400
the conservative mixing curve.
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3.4. Water to atmosphere CO2 and CH4 fluxes
403
Generally, the empirical models of C96 and J08 showed good agreement (Table 2). The W14
404
model always estimated a lower CO2 or CH4 flux compared to C96 and J08 but with a
405
discrepancy of < 50%, therefore fluxes are presented as an average of the three empirical
406
models (Table 2). Overall, average wet and dry season CO2 fluxes were similar in the JR
407
estuary (75.3 ± 5.2 mmol m-2 d-1) and in the FR estuary (70.0 ± 6.7 mmol m-2 d-1), and were
408
approximately 50% lower in the CC estuary (36.1 ± 5.0 mmol m-2 d-1). Average wet and dry
16
ACCEPTED MANUSCRIPT season CH4 fluxes were also highest in the JR estuary (779.3 ± 44.9 µmol m-2 d-1), and lower
410
in the CC estuary (118.8 ± 27.8 µmol m-2 d-1) and FR estuary (99.2 ± 7.1 µmol m-2 d-1). The
411
microbubble flux (FMB) contributed more to total CH4 fluxes (FCH4) in the wet season
412
compared to the dry season in the three estuaries. In the FR in the dry season, the estimated
413
microbubble flux showed slightly negative values due to the lower CH4 saturation and
414
temperature, hence was insignificant or absent in the FR dry season (Table 2). Average CO2
415
and CH4 fluxes were approximately 50% higher in the wet season compared to the dry season
416
in the three estuaries. An exception was the CO2 flux in the CC estuary, where an inverse
417
trend was found with an average CO2 flux approximately 60% higher in the dry season
418
compared to the wet season, which was related to the increased pCO2 at the CC estuary
419
mouth in the dry season (Figure 2).
420
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3.5. Groundwater observations
422
Radon concentrations were only available for the dry season and ranged from 1,198 to 24,661
423
dpm m-3 in the JR estuary, from 476 to 3,910 dpm m-3 in the FR estuary, and from 2,803 to
424
4,230 dpm m-3 in the CC estuary (Figure 5). Because 222Rn was measured every 10 minutes,
425
only three
426
estuary is excluded from the graphical illustration in Figure 5. An inverse trend was found
427
between
428
towards lower salinities in the JR and FR (Figure 5), and likely in the CC estuary. In the JR
429
estuary, a positive relationship was found between
430
0.001) and between
222
431
relationship between
222
432
pronounced (pCO2: R2 = 0.24, n = 44, p < 0.001; CH4: R2 = 0.29, n = 44, p < 0.001) and
433
elevated pCO2 was observed around low 222Rn concentrations (Figure 5).
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Rn measurements were available for the CC estuary, therefore
Rn concentration and salinity, showing generally higher
222
222
Rn in the CC
222
Rn concentrations
Rn and pCO2 (R2 = 0.60, n = 29, p <
Rn and CH4 (R2 = 0.89, n = 29, p < 0.001). In the FR estuary, the Rn and pCO2 and between
222
Rn and CH4 was also positive but less
17
ACCEPTED MANUSCRIPT 434 3.6. Flushing times and the contribution of riverine ventilation to total emissions
436
The freshwater flushing and the tidal currents greatly influence the freshwater fractions in
437
each estuary and season. The tidal amplitude was low (2.1 m) in the JR and approximately
438
4.0 m in the FR and CC estuaries. The daily river discharge was significantly higher during
439
the surveys of the wet season (FR: 6,356 ML d-1; JR: 10,863 ML d-1) compared to the surveys
440
of the dry season (FR:139 ML d-1; JR: and 2,192 ML d-1). The freshwater flushing time in the
441
FR was 72.8 days in the dry season and 5.7 days in the wet season. In the JR estuary, the
442
flushing times were significantly shorter with 2.3 days in the dry season and 0.6 days in the
443
wet season. The riverine contribution was < 100% in all cases except the JR wet survey,
444
indicating that overall emissions of CO2 (JR dry: 38.1%; FR wet: 12.9%; FR dry: 1.5%) and
445
CH4 (JR dry: 52.9%; FR wet: 5.4%; FR dry: 0.9%) were partially related to processes within
446
the estuary or groundwater inputs rather than from riverine ventilation. In the JR estuary in
447
the wet season, the contribution of riverine ventilation of CO2 (311.0%) and CH4 (174.7%)
448
exceeded 100% suggesting that the remaining CO2 and CH4 was exported to the coastal
449
ocean (Figure 6). The contributions of riverine CO2 and CH4 to total estuarine emissions in
450
the three estuaries were higher in the wet season compared to the dry season (Figure 6).
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4. Discussion
453
4.1. Comparison of seasonal CO2 and CH4 emissions with global and other Australian
454
estuaries
455
The three mangrove-dominated estuaries in tropical Queensland have distinct differences in
456
catchment size, hydrology and geomorphology, thus cover a large range of estuarine and
457
coastal settings. The supersaturated levels in the surface water and the water to atmosphere
458
fluxes showed that the three estuaries were a source of CO2 and CH4 to the atmosphere
18
ACCEPTED MANUSCRIPT during the wet and dry season field campaigns. CO2 emissions from the JR, FR, and CC
460
estuaries were within the range or towards the upper end of global average CO2 emissions
461
from estuaries (7.74 to 35.71 mol m-2 y-1; Abril and Borges, 2005; Borges, 2005; Borges et
462
al., 2005; Cai, 2011; Chen et al., 2013, 2012; Chen and Borges, 2009; Laruelle et al., 2010)
463
(Table 3). Emission of CO2 in the CC estuary were similar to the average CO2 emission
464
proposed for subtropical and tropical estuaries (16.8 mol m-2 y-1; Borges et al., 2005),
465
whereas the JR and the FR estuaries showed slightly higher emissions (Table 3). Similar to
466
CO2, CH4 emissions from the FR and CC estuaries were also within the range of global
467
estuary emissions, whereas the emissions from the JR estuary were at the high end of global
468
estimates (Bange et al., 1994; Borges and Abril, 2011; Middelburg et al., 2002; Upstill-
469
Goddard et al., 2000). An overall average of ~ 200 mmol m-2 yr-1 from the three mangrove-
470
dominated estuaries in Queensland fits well with the higher estimate of 266 mmol m-2 y-1 for
471
all estuarine types suggested by Borges and Abril (2011).
472
A comparison of estuary CO2 emissions over latitudinal regions showed CO2 emissions can
473
vary significantly (Chen et al., 2013). Estuaries between the latitudes 23.5 and 50 °N have
474
higher CO2 emissions (63.3 ± 100.7 mmol m-2 d-1) compared to low latitudinal regions (0 to
475
23.5 °S: 44.1 ± 29.3 mmol m-2 d-1; 0 to 23.5 °N: 38.8 ± 55.4 mmol m-2 d-1), and are the lowest
476
at latitudes > 50 °N and °S (Chen et al., 2013). Including the three tropical mangrove-
477
dominated estuaries from this study, the revised global estimate for the latitudinal region 0 to
478
23.5 °S is 52.1 ± 16.1 mmol m-2 d-1, which is an increase of 15% compared to the estimate of
479
Chen et al. (2013). No such latitudinal estimates are available for estuary CH4 emissions and
480
combined CH4 emissions of estuaries, lakes, oceans, streams and wetlands did not show any
481
significant trends across latitudes and climatic zones (Ortiz-Llorente and Alvarez-Cobelas,
482
2012). However, CH4 emissions from sediments and waters in coastal mangrove tidal creeks
483
showed increased emissions at mid latitudes between 20 and 25 °N and °S, which is similar
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ACCEPTED MANUSCRIPT to the latitudinal area of the three studied estuaries here (17.5 to 23.5 °N and °S) (Rosentreter
485
et al., 2018b).
486
Since these global estimates of estuary CO2 and CH4 emissions, a number of new studies
487
have been published from the eastern coast of Australia (Table 3). The CO2 and CH4
488
emissions from the JR, FR and CC estuaries lay within the range or at the top end for
489
Australian estuaries. The degree of disturbance and stress factors in the river catchment
490
influences overall emissions of an estuary, because increased riverine and terrestrial organic
491
carbon inputs fuel net heterotrophy in the estuary zone. The large range of CO2 (-11.2 to
492
869.4 mmol m-2 d-1) and CH4 (7 to 25,800 µmol m-2 d-1) emissions between estuarine systems
493
in Australia can be attributed to the various features that characterise these estuaries. For
494
example, in the highly urbanised Sydney Harbour estuary, the CO2 efflux to the atmosphere
495
ranged from 1.2 to 5 mmol m-2 d-1 (Tanner et al., 2017) and in the urbanised Brisbane estuary
496
CH4 emissions ranged from 136 to 2,603 µmol m-2 d-1 (Sturm et al., 2017, 2016). In contrast,
497
three relatively undisturbed seagrass-dominated estuaries in Australia were net autotrophic
498
and a sink for atmospheric CO2 (-3 to -11.2 mmol m-2 d-1; Maher and Eyre, 2012). In
499
estuaries, net autotrophy is mainly related to aquatic submerged vegetation and water surface
500
area, and has been mostly observed in shallow estuaries (Caffrey, 2004; Eyre et al., 2011;
501
Ferguson and Eyre, 2010; Maher and Eyre, 2012; Santos et al., 2004). Exceptional high
502
emissions of CO2 (and CH4) in Australia were found in estuarine systems adjacent to
503
modified acidic floodplain wetlands (Ruiz-Halpern et al., 2015) or estuaries with a significant
504
contribution of groundwater inputs (Atkins et al., 2013; Sadat-Noori et al., 2015a). Korogoro
505
Creek, for example, is a surface expression of a wetland groundwater table (Sadat-Noori et
506
al., 2015a) and the North Creek study was conducted near headwaters (Atkins et al., 2013),
507
thus groundwater inputs were elevated at these study locations. The relatively high emissions
508
from the three mangrove dominated JR, FR an CC estuaries are likely controlled by a
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combination of factors, which appear to shift along different parts of the estuary along the
510
salinity gradient and between seasons, and will be discussed separately for CO2 and CH4 in
511
the following sections.
512 Seasonal variability of carbon components was prominent in the mangrove-dominated
514
estuaries. CO2 and CH4 emissions were higher in the wet season compared to the dry season
515
in the JR and FR estuaries and driven by higher wind speeds and higher surface water gas
516
concentrations in the wet season. In contrast, surface water pCO2 and CO2 emissions in the
517
CC estuary were lower in the wet season than in the dry season (Figure 2). The increased
518
pCO2 in the CC in the dry season was likely derived from organic matter decomposition on
519
the extensive inter-tidal mud flats, which are found at the outer estuary mouth. This was the
520
only location where pCO2 and CO2 emissions were found elevated at the downstream transect
521
of the estuary surveys (Figure 2). DIC showed an opposite trend with significantly higher
522
concentration in the dry season in the three estuaries. High dry season DIC values were also
523
found in the Pearl River estuary in China and related to a dilution effect during the wet
524
season due to higher river discharge (Guo et al., 2008). The shifting between two mixing
525
regimes and the variation of end-member DIC (and alkalinity) between the dry and wet
526
season were responsible for complex inorganic carbon patterns in the estuarine waters. DOC
527
concentrations were higher in the wet season in the three estuaries, indicating higher
528
terrestrial carbon inputs most likely due to enhanced surface runoff in the rainy season
529
(Figure 1). Similarly, the contribution of riverine CO2 and CH4 to total emissions was higher
530
in the wet season. Distinct seasonal differences of CO2 and CH4 emissions can be of
531
importance for annual estimates. For example, CO2 and CH4 in the JR estuary was fully
532
ventilated within the estuary in the dry season but exported to the ocean in the wet season
533
(Figure 6).
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ACCEPTED MANUSCRIPT 534 4.2. Factors controlling estuarine CO2 emissions
536
In estuaries, CO2 cycling is more complex than in headwater streams and rivers because of
537
the various lateral inputs from rivers, groundwater and surface runoff, as well as in situ
538
production and the exchange with the atmosphere and the adjacent coastal ocean. In the dry
539
season, the relationship between pCO2/δ13C-CO2 and salinity suggests that mixing of
540
freshwater rich in CO2 and oceanic water rich in DIC and alkalinity was an important driver
541
of the distribution of pCO2 along the three estuaries (Figure 3 and 4). In the wet season,
542
however, sources and sinks of pCO2 and the stable isotopic ratio were more variable along
543
the estuarine salinity gradients, which highlights the different controls on CO2 cycling
544
between seasons. The positive relationship between
545
(Figure 5) further suggests that high surface water pCO2 in the upper estuaries was likely
546
driven by CO2 enriched groundwater inputs, although another co-varying factor such as
547
mixing cannot be excluded. Both, 222Rn and pCO2 increased with decreasing salinity towards
548
upstream riverine freshwater sections (Figure 3 and 5). The relationship between
549
pCO2 was more pronounced in the JR estuary (R2 = 0.60, p < 0.001) than in the FR estuary
550
(R2 = 0.24, p < 0.001). The elevated pCO2 at low
551
peaking around mid-salinities suggests that groundwater inputs were relatively low in the
552
upper FR estuary (where pCO2 was high) and inputs were higher in the mid-estuary (Figure
553
5). Although 222Rn was only available for the dry season in this study we expect an enhanced
554
contribution of groundwater inputs in the wet season in the three estuaries (Sadat-Noori et al.,
555
2015b).
556
Freshwater CO2 in this study showed depleted δ13C values around ~ -17 ‰, which reflects
557
the isotopic effect of the terrestrial carbon cycle, whereas the marine CO2 was more
558
distributed around a mean of ~ -10 ‰ (Table 1, Figure 4). The fairly abrupt change and
222
222
Rn (groundwater tracer) and pCO2
222
Rn and
Rn concentrations along with
222
Rn
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ACCEPTED MANUSCRIPT distinct depletion of δ13C-CO2 values scattered around the end-member in the FR dry season
560
may be indicative of mixing with other carbon sources i.e. benthic macroalgae (-23.1 to -16.4
561
‰), marine phytoplankton (-22.0 to -20.0 ‰), or a mangrove-derived carbon source (-35 to -
562
25 ‰) (Bouillon et al., 2008, 2007). Indeed, pCO2 and CO2 emissions from mangrove tidal
563
creeks in the JR and FR estuaries were significantly higher than from the adjacent main
564
estuary channel (64.4 to 205.2 mmol m-2 d-1; Rosentreter et al., 2018a) and tidal exports of
565
mangrove waters enriched in inorganic carbon components were likely a carbon source to the
566
main estuaries. However, non-conservative changes in δ13C-CO2 may also be related to
567
equilibrium and kinetic isotope fractionation i.e. dehydration and degassing of CO2 into the
568
atmosphere (Marlier and O’Leary, 1984; Miyajima et al., 2009; Zhang et al., 1995). Other
569
naturally occurring processes associated with kinetic fractionation, such as abiotic or
570
biogenic precipitation of CaCO3 (Romanek et al., 1992; Turner, 1982), or photosynthetic CO2
571
fixation into organic matter (Descolas-Gros and Fontugne, 1990), may also be responsible for
572
a relative enrichment of δ13C-CO2 compared to conservative mixing.
573
DOC and pCO2 have been found to have a consistent positive relationship in several
574
temperate and tropical tidal rivers and can be indicative of terrestrial organic matter inputs or
575
lateral inputs from surface runoff driving net heterotrophy and CO2 production (Borges and
576
Abril, 2011). While a strong positive relationship between DOC and pCO2 suggests a
577
connection between terrestrial organic carbon and surface water pCO2 in the FR and CC
578
estuaries, terrestrial OM inputs were not an important factor controlling CO2 emissions in the
579
JR estuary (Figure 1). In fact, the contribution of riverine CO2 to overall CO2 emissions was
580
higher in the JR estuary compared to the FR estuary. This is likely related to the short
581
residence time, which enhances the relative importance of riverine CO2 to total emissions.
582
The particular short freshwater flushing times in the JR estuary in the wet season (0.6 days),
583
freshwater flushing to the estuary mouth (salinity ~12) in combination with the high
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585
adjacent ocean. The difference of riverine excess CO2 and the emitted CO2 within the estuary
586
is 6.13 × 105 mol d-1, or in other words, 32% of the riverine CO2 was lost via gas exchange
587
within the estuary and the remaining 68% were likely exported to the ocean. In contrast,
588
flushing times in the FR estuary were long, particularly in the dry season (72.8 days), and
589
CO2 derived from the upstream river was fully ventilated within the estuary. The three
590
tropical estuaries are characterised by episodic and large freshwater inputs during the wet
591
season and low or no discharge and high evaporation rates during the dry season. Therefore,
592
the contribution of riverine CO2 to overall emissions was distinct in the wet and dry season
593
but within the range of nine other European and two U.S. estuaries (Figure 6). Borges and
594
Abril (2011) proposed that the contribution of riverine CO2 to total estuary emissions is about
595
10%, and the remaining 90% of the estuary emissions may be attributed to net heterotrophy.
596
Similarly, an average riverine contribution of 18% (range 2 to 38%) was found for the FR
597
estuary and the JR estuary in the dry season. We attribute the remaining contribution to a
598
combination of in situ production within the estuary, groundwater discharge enriched in CO2,
599
and tidal export from adjacent coastal ecosystems. The exceptional high contribution of
600
riverine CO2 in the JR in the wet season is similar to that of the Rhine in Europe with similar
601
short residence times of 1 to 3 days, which implies that most of the organic matter was
602
flushed to the estuary mouth before it could be mineralized within the estuary. Unfortunately,
603
flushing times and riverine contributions of CO2 could not be estimated for the CC estuary
604
because of the lack of river discharge data. However, we expect relatively short freshwater
605
flushing times < 5 days because of the smaller catchment size relative to surface area in the
606
CC estuary and moderate exports of CO2 to the ocean in the wet season.
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607 608
4.3. Factors controlling estuarine CH4 emissions
24
ACCEPTED MANUSCRIPT The downstream decrease of CH4 concentrations along the salinity gradient found in the JR,
610
CC and FR (Figure 3) is typical for estuaries and related to the loss of riverine CH4 due to
611
estuary emissions, microbial oxidation, and the mixing of riverine water with oceanic water
612
low in CH4 (Borges and Abril, 2011; Borges et al., 2018b; Rhee et al., 2009; Upstill-Goddard
613
and Barnes, 2016). With regard to estuary emissions, there are several pathways for CH4 to
614
reach the atmosphere from the sediment and the water column. The dominant process -
615
passive diffusion- occurs at the sediment-water and water-atmosphere interface. However,
616
there are also several non-diffusion processes. Firstly, a microbubble flux across the water-
617
atmosphere interface induced by microbubble entrainment of surface waters or formed in situ
618
under surface films or on suspended particles in supersaturated environments has been
619
highlighted recently (Beaulieu et al., 2012; McGinnis et al., 2015; Prairie and del Giorgio,
620
2013; Rosentreter et al., 2017; Woolf et al., 2007). The microbubble flux has been proposed
621
to explain an enhanced gas transfer velocity of CH4 relative to CO2 in mangrove dominated
622
estuaries (Rosentreter et al., 2017) and an increased transfer velocity up to 2.5-fold in lakes
623
(McGinnis et al., 2015; Prairie and del Giorgio, 2013). The total CH4 emissions in the JR, FR
624
and CC estuaries account for the contribution of a microbubble flux, but the microbubble flux
625
may still be underestimated as we could not include current velocity as a factor in the
626
equation (Eq.6, Table 2). An enhanced microbubble flux contribution in the wet season in the
627
three estuaries can be explained by the higher CH4 surface water concentrations, higher wind
628
speeds and increased water temperature (Australian summer). Furthermore, ebullition (rising
629
gas bubbles from sediments), active or passive plant-mediated transport, and the process of
630
tidal pumping can be important pathways of CH4 to reach the atmosphere in estuaries (Barber
631
et al., 1988; Kelley et al., 1995, 1990; Maher et al., 2015; Purvaja et al., 2004). These
632
pathways were not determined in this study and total CH4 emissions must be seen as a lower
633
limit.
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ACCEPTED MANUSCRIPT There was a positive correlation between pCO2 and CH4 in all three estuaries, suggesting a
635
common source of the two gases (Figure 7). For similar pCO2, the CH4 concentrations were,
636
however, higher in the JR estuary compared to the FR estuary and the CC estuary in the dry
637
season. STPs can be found in both, the JR and the FR catchments but the STP in the JR is
638
geographically much closer to the estuarine section surveyed, thus sewage discharge may
639
have also contributed to the increase of CH4 concentrations (and pCO2) in the JR estuary. The
640
strong relationship between
641
groundwater inputs highly enriched in CH4. Diffusive CH4 fluxes in the upper section in three
642
surveys in the North Creek estuary were also driven by CH4 enriched groundwater, either
643
directly or indirectly (Maher et al. 2015). But as mentioned above, co-variance with mixing
644
cannot be excluded. The relationship between DOC and CH4 concentrations was weak in the
645
JR estuary, but similarly to the relationship between DOC and pCO2, stronger in the FR and
646
CC estuaries, suggesting that CH4 concentration in the surface water of these estuaries was
647
also driven by terrestrial carbon inputs (Figure 1).
648
The isotopic ratio of CH4 is different for freshwater and marine environments. A rough
649
boundary around -60 ‰ can be drawn, with a mean of -59 ‰ for biogenic CH4 in freshwater
650
and a mean of -68 ‰ for marine sedimentary environments (Whiticar et al., 1986). Co-
651
existing CO2-CH4 carbon stable isotope pairs indicate methane production was derived from
652
hydrogenotrophic or acetoclastic methanogenesis, with a shift towards methane oxidation in
653
the wet season (Figure 7). Methanogenesis by carbonate reduction has a larger CO2-CH4
654
isotope separation (saline or marine region), whereas acetoclastic methanogenesis (methyl-
655
type fermentation) or CH4 consumption have a smaller isotope separation, hence lower
656
carbon fractionation factor values (freshwater region) (Whiticar, 1999). Indeed, a clear
657
separation of isotope pairs was found between the two seasons in the JR estuary. While in the
658
dry season, carbonate reduction indicative of a more saline/marine environment was the
Rn and CH4 concentrations in the JR estuary suggests
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ACCEPTED MANUSCRIPT dominant CH4 producing process, methyl-fermentation indicative of a freshwater/riverine
660
environment was the dominant process in the wet season. The same seasonal separation
661
although less pronounced was found in the FR and CC estuaries. However, without further
662
evidence from hydrogen isotopes (δD-H2O, δD-CH4&, this result must be taken with caution
663
because of the isotopic fractionation during diffusion (kinetic, equilibrium fractionation),
664
advection, transport, and mixing with other carbon sources (Whiticar and Schaefer, 2007;
665
Whiticar et al., 1986).
666
The riverine contribution of CH4 to overall CH4 emissions was generally less pronounced
667
than the riverine contribution of CO2 to total CO2 emissions in the JR and FR estuary (Figure
668
6). In the dry season in the JR estuary and in both seasons in the FR estuary, riverine CH4
669
was fully ventilated within the estuary, suggesting that the remaining 80% (range 47 to 99%)
670
of the total emissions were driven by in situ processes within the estuary, and/or lateral
671
groundwater inputs. High CH4 concentrations and emissions were found in adjacent tidal
672
mangrove creeks in the JR and FR estuaries (average CH4 flux ranged from 96.5 to 1,049.8
673
µmol m-2 d-1; Rosentreter et al., 2018b) suggesting tidal exports from mangrove creeks to the
674
estuary main channel may have further contributed to overall emissions in the estuaries. Only
675
in the wet season in the JR estuary, an export of riverine CH4 to the open ocean is expected.
676
A comparison of the excess riverine CH4 and the emitted CH4 within the JR estuary suggests
677
that 57% of the riverine CH4 was lost via gas exchange in the estuary, and the remaining 43%
678
(or 2.06 × 103 mol d-1 CH4) was exported to the adjacent ocean. The relative enriched δ13C-
679
CH4 values compared to the conservative mixing support the hypothesis of enhanced riverine
680
CH4 contribution in the rainy season in the JR, as these values indicate a more riverine origin
681
(Figure 4 and 7). Furthermore, the salinity of the oceanic end-member at the estuary mouth
682
was relatively fresh (~ 12), which also indicates a strong freshwater source from upstream.
683
This is the first time that the riverine CH4 contributions to overall CH4 emissions are
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estimated for estuaries and it remains to be established if the lower contribution of CH4
685
compared to riverine CO2 contribution to overall emissions is a general pattern.
686 5. Conclusion
688
The three tropical mangrove-fringed estuaries at the north-eastern coast of Queensland were
689
supersaturated in CO2 and CH4 with respect to the atmosphere. Emissions were higher in the
690
wet season compared to the dry season and within or at the upper end of the range for
691
estuaries in Australia and globally. Factors controlling the CO2 and CH4 emissions varied
692
spatially and seasonally. Groundwater inputs and riverine carbon inputs were likely the main
693
factors controlling CO2 and CH4 emissions in the JR estuary, while in situ production and
694
terrestrial carbon inputs were the more important drivers of emissions in the FR and CC
695
estuaries. The exchange with adjacent coastal tidal ecosystems (mangroves, inter-tidal flats)
696
likely contributed to overall CO2 and CH4 emissions in all three estuaries. The estimation of
697
the percent contribution of riverine ventilation to overall estuary emissions suggests that the
698
riverine contribution is more important for estuarine CO2 than CH4. The seasonal and inter-
699
site variability of CO2 and CH4 emissions as well as the various carbon sources controlling
700
the emissions from the three mangrove-dominated estuaries emphasises the need for further
701
studies on carbon cycling in estuaries in Australia, and globally. This will help to better
702
predict the amount of CO2 and CH4 that is ventilated within the estuary and/or exported to the
703
open ocean – a prediction of great importance for the coastal global ocean under future
704
climate change scenarios.
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6. Acknowledgments
707
We thank Mitchell Call and Ashly McMahon for their assistance in the field. This project
708
was funded by the Great Barrier Reef Foundation’s Resilient Coral Reefs Successfully
28
ACCEPTED MANUSCRIPT 709
Adapting to Climate Change research and development program in collaboration with the
710
Australian Government, and by Australian Research Council Grants DE150100581,
711
DP160100248, and LP150100519.
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ACCEPTED MANUSCRIPT References
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Abril, G., Borges, A.V., 2004. Carbon dioxide and methane emissions from estuaries, in: Greenhouse Gas Emissions: Fluxes and Processes. Springer Berlin Heidelberg, pp. 187–207.
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TE D
972
38
ACCEPTED MANUSCRIPT
Table 1 Average (range) of temperature, salinity, pH, DO, wind speed (U10), DOC, DIC, pCO2 and CH4 concentration and stable isotopes in the three estuaries. Salinity
pH
LDO (%)
U10 (m s-1)
DOC (mg L-1)
DIC (µmol L-1)
pCO2 (µatm)
δ13C-CO2 (‰)
CH4 (nmol L-1)
δ13C-CH4 (‰)
25.0 (24.2 - 25.8)
0.9 (0.1 - 12.3)
6.28 (5.95 - 6.99)
81 (74 - 89)
3.8 (0 - 6.1)
1.8 (1.5 - 2.3)
348 (134 - 1,025)
2,275 (502 - 2,924)
-15.77 (-16.88 - -11.66)
420.4 (185.4 - 529.7)
-47.72 (-49.92 - -46.06)
27.4 (26.2 - 28.3)
14.1 (0.03 - 34.4)
7.27 (6.69 - 7.70)
98 (93 - 114)
3.1 (0 - 5.8)
0.6 (0.5 - 1.3)
1,038 (361 - 1,982)
1,113 (409 - 2,880)
-15.00 (-17.34 - -9.95)
179.0 (3.8 - 507.8)
-50.67 (-62.52 - -45.96)
26.8 (26.2 - 27.9)
27.8 (11.6 - 35.0)
7.10 (6.80 - 7.90)
90 (85 - 99)
4.7 (3.1 - 6.1)
25.7 (25.4 - 25.9)
33.1 (30.7 - 34.4)
7.32 (7.07 - 7.51)
98 (89 - 104)
6.3 (4.7 - 7.2)
12.9 (0.2 - 28.8)
7.63 (7.36 - 7.84)
92 (86 - 97)
29.8 (21.6 - 34.6)
7.04 (6.79 - 7.28)
99 (93 - 114)
JR wet
CC wet
FR wet 28.0 (26.9 - 30.1)
980
704 (449 - 1,216)
-11.10 (-15.86 - -8.84)
52.8 (9.6 - 459.0)
-61.96 (-70.01 - -49.43)
1.5 (0.8 - 3.7)
2,870 (2,426 - 3,287)
942 (590 - 1,632)
-12.04 (-15.33 - -9.21)
26.2 (6.5 - 95.4)
-58.74 (-61.54 - -52.84)
6.3 (2.9 - 9.9)
4.7 (1.4 - 8.3)
2.6 (1.2 - 4.0)
1,842 (576 - 4,387)
2,305 (2,230 - 2,349)
1,095 (618 - 2,505)
1,139 (710 - 1,672)
-13.29 (-18.67 - -9.67)
-13.29 (-17.28 - -10.75)
27.5 (12.9 - 50.0)
25.6 (3.3 - 96.5)
-52.76 (-57.85 - -37.45)
-54.78 (-61.23 - -50.05)
AC C
21.8 (21.2 - 22.3)
2,043 (1,790 - 2,124)
7.1 (3.6 - 10.3)
EP
FR dry
3.1 (2.2 - 5.5)
TE D
CC dry
M AN U
JR dry
RI PT
Temp (°C)
SC
978 979
39
ACCEPTED MANUSCRIPT
Table 2 Estuary CO2 and CH4 water to atmosphere fluxes (± C.I. 95%) in the wet and in the dry season. JR dry
CC wet
CC dry
Wanninkhof (2014)
70.8 ± 4.5
25.5 ± 3.3
16.1 ± 2.4
Carini et al. (1996)
136.5 ± 6.6
49.7 ± 5.7
25.0 ± 3.5
Jiang et al. (2008)
124.0 ± 6.0
45.4 ± 5.3
23.7 ± 3.4
Average
110.4 ± 5.6
40.2 ± 4.7
Wanninkhof (2014) + FMB
792.4 ± 34.3
398.0 ± 38.8
Carini et al. (1996) + FMB
1,212.7 ± 46.5
Jiang et al. (2008) + FMB
FR dry
43.1 ± 5.9
87.7 ± 11.2
31.2 ± 1.4
51.9 ± 7.0
90.4 ± 10.3
51.7 ± 2.0
56.3 ± 7.6
109.6 ± 13.5
49.3 ± 1.9
21.6 ± 3.1
50.5 ± 6.8
95.9 ± 11.6
44.1 ± 1.8
130.0 ± 29.9
65.4 ± 16.5
148.3 ± 9.7
27.4 ± 3.3
584.8 ± 55.6
180.5 ± 40.2
78.7 ± 20.0
152.4 ± 8.6
48.4 ± 5.2
1,136.3 ± 42.1
551.71 ± 52.3
173.3 ± 38.7
84.8 ± 21.1
173.8 ± 10.8
45.1 ± 4.9
Average
1,047.1 ± 40.8
511.5 ± 48.9
161.3 ± 36.3
76.3 ± 19.2
158.1 ± 9.7
40.3 ± 4.4
(Microbubble flux contribution)
(345.4 ± 11.6)
EP
M AN U
SC
Average CO2 flux (mmol m-2 d-1)
982
FR wet
RI PT
JR wet
(39.5 ± 11.6)
(2.4 ± 2.2)
(47.9 ± 4.6)
-
TE D
Average CH4 flux (µmol m-2 d-1)
(201.7 ± 17.6)
AC C
981
40
ACCEPTED MANUSCRIPT
Table 3 Comparison of CO2 and CH4 flux studies in Australian estuaries from low to high latitudes. pCO2 (µatm)
CO2 flux (mmol m-2 d-1)
CO2 flux (mol m-2 y-1)
Johnstone River Estuary
17° S
mangroves
409 - 2,924
40.2 - 110.4
15 - 40
Constant Creek Estuary
20° S
mangroves
449 - 1,632
21.6 - 50.5
8 - 18
Fitzroy River Estuary
23° S
mangroves
618 - 2,505
44.1 - 95.9
16 - 35
Shark Bay
26° S
hypersaline
350 - 420
2.0
0.7
Brisbane River Estuary
27° S
urban
Brisbane River Estuary
27° S
urban
Brisbane River Estuary
27° S
urban, 2013
Brisbane River Estuary
27° S
urban, 2014
Broadwater Estuary
27° S
urban
Caboolture River Estuary
27° S
modified, wetlands
Caboolture River Estuary
27° S
modified, wetlands
North Creek Estuary
28° S
Richmond River Estuary
29° S
Coffs Creek Estuary
CH4 flux (µmol m-2 d-1)
M AN U
CH4 flux (mmol m-2 y-1)
Reference
3.8 - 530
512 - 1,047
187 - 382
This study
6.5 - 459
76 - 161
28 - 59
This study
3.3 - 97
40 - 158
15 - 58
This study Smith and Atkinson, (1983)
48 - 687
193 - 775
70 - 283
Sturm et al., (2016)
81 - 647
136 - 578
50 - 211
Sturm et al., (2017)
119 - 908
246 - 2,603
90 - 950
Sturm et al., (2017)
31 - 578
19 - 1,744
7 - 637
Musenze et al., (2014)
2.9 - 13.7
1-5
Macklin et al., (2014)
0.1 - 0.3
0.04 - 0.1
Adiyanti et al., (2016)
37 - 278
14 - 102
Jeffrey et al., (2018b)
TE D
28° S
373 – 7,136 501 - 11,151
799
292
500 - 12,000
19.3 - 69.7
7 - 25
acidic wetlands
380 - 1,196
252.1
92
30° S
urban
403 – 7,920
24.1 – 94.9
9 - 35
Camden Haven
31° S
seagrass
166 - 757
-3 - -8
-1.8
Maher and Eyre, (2012)
Hasting River Estuary
31° S
seagrass
210 - 1,823
-3 - -5
-0.4
Maher and Eyre, (2012)
Korogoro Creek Estuary
31° S
mangroves, groundwater
248 - 25,135
869.4
317
Wallis Lake
32° S
seagrass
142 - 791
-11.2 - 3.5
-2
Sydney Harbour Estuary
33° S
urban
173 - 5,650
1.2 - 5
0.4 - 1.8
Yarra River Estuary
37° S
salt wedge
519 – 3,395
17.5 – 39.0
6 - 14
EP
North Creek Estuary
342 - 5,928
agriculture, mangroves agriculture, mangroves
CH4 (nmol L-1)
RI PT
Feature
SC
Latitude
Estuary
AC C
983
Atkins et al., (2013) 1.8 - 150
7 - 51
3 - 19
Maher et al., (2015) Ruiz-Halpern et al., (2015)
2 - 687
3-5
39 - 193
25,800
14 - 70
9,417
Jeffrey et al., (2018a)
Sadat-Noori et al., (2015a) Maher and Eyre, (2012) Tanner et al., (2017)
47 – 1,303
110 - 840
40 - 307
Tait et al., (2017)
984
41
ACCEPTED MANUSCRIPT Figure 1
RI PT
985
Figure 1 DOC concentrations versus (a) pCO2 and (b) CH4 concentrations in the JR estuary, CC estuary and FR estuary. The lines represent the linear regression lines.
M AN U
987 988 989
SC
986
990 991 992
996 997 998 999 1000
EP
995
AC C
994
TE D
993
1001
42
ACCEPTED MANUSCRIPT Figure 2
1003 1004 1005 1006 1007
AC C
EP
TE D
M AN U
SC
RI PT
1002
Figure 2 pCO2 and CH4 concentration gradients in the JR estuary, the CC estuary and the FR estuary. The left panel shows the wet season, the right panel shows the dry season, respectively. Average CO2 and CH4 emissions over the estuary surveys from Table 2 are presented in each graph.
1008
43
ACCEPTED MANUSCRIPT Figure 3
1017
Figure 3 Longitudinal distribution of pCO2 and CH4 along the salinity gradient in the JR estuary, CC estuary and FR estuary. pCO2 and CH4 concentrations lower than predicted by the conservative mixing lines (black dotted line) indicate a sink (or loss) along the salinity gradient. Concentrations above the mixing lines indicate a source of CO2 or CH4.
EP
1011 1012 1013 1014 1015 1016
AC C
1010
TE D
M AN U
SC
RI PT
1009
44
ACCEPTED MANUSCRIPT Figure 4
1021 1022 1023 1024 1025 1026 1027
Figure 4 Longitudinal distribution of δ13C-CO2 and δ13C-CH4 along the salinity gradient in the JR estuary, CC estuary and FR estuary. The conservative mixing curves (black dotted line) show an increased function if δO > δR and a decreased function if δO < δR. δ13C-CO2 and δ13C-CH4 values in the three estuaries follow conservative mixing, are depleted (below) or enriched (above) relative to the freshwater and oceanic end-members.
EP
1020
AC C
1019
TE D
M AN U
SC
RI PT
1018
45
ACCEPTED MANUSCRIPT Figure 5
SC
RI PT
1028
1030 1031 1032 1033 1034
M AN U
1029
Figure 5 Groundwater (222Rn) over the salinity gradient a) in the JR estuary and b) in the FR estuary, and the correlation between 222Rn and pCO2 and CH4 c) in the JR estuary and d) in the FR estuary in the dry season. The 222Rn concentrations in the CC estuary are not illustrated in this figure because only three data point were available for 222Rn.
EP
1037
AC C
1036
TE D
1035
46
ACCEPTED MANUSCRIPT 1038
Figure 6 1039 1040 1041
RI PT
1042 1043 1044
EP
TE D
M AN U
Figure 6 Contribution (as in %) of the riverine ventilation of a) CO2 and b) CH4 to the overall emissions in the JR estuary (dark green) and FR estuary (light green) in the wet and dry season. The percent contribution is calculated from the riverine load and the estuary areaweighted emissions (see Eq. 10). The data of the nine European estuaries and two US estuaries are derived from Borges and Abril (2011): Rhine (Rh), Randers Fjord (Ra), Loire (Lo), Elbe (El), Sado (Sad), Ems (Em), York River (YR), Thames (Th), Gironde (Gi), Satilla (Sat), and Scheldt (Sch). If the riverine contribution exceeds the total emissions from within the estuary (above 100% line), the remaining CO2 or CH4 is exported to the open ocean. The graph 6a) was adapted from Borges and Abril (2011).
AC C
1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056
SC
1045
47
ACCEPTED MANUSCRIPT 1057
Figure 7
SC
RI PT
1058
Figure 7 Comparison of a) pCO2 versus CH4 concentrations in the JR estuary, in the CC estuary and in the FR estuary in the wet and dry season, and b) δ13C-CO2 versus δ13C-CH4. The dashed lines are the carbon fractionation factor lines that indicate the proposed boundaries between hydrogenotrophic methanogenesis (saline, marine region), acetoclastic methanogenesis (freshwater region), and methane oxidation (Whiticar, 1999; Whiticar and Faber, 1986).The concentrations and δ13C data in the JR are shown for the main arm and south arm surveys.
TE D
1060 1061 1062 1063 1064 1065 1066 1067
M AN U
1059
1068
EP
1069 1070
1072 1073 1074
AC C
1071
1075 1076 1077 1078
End of Article
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