| Citation: | Weizhen Jiang, Guizhi Wang, Qing Li, Manab Kumar Dutta, Shilei Jin, Guiyuan Dai, Yi Xu. The fate of carbon resulting from pore water exchange in a mangrove and Spartina alterniflora ecozone[J]. Acta Oceanologica Sinica, 2023, 42(8): 61-76. doi: 10.1007/s13131-023-2234-2
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Mangroves are a remarkable blue carbon sink system on Earth with a global carbon storage of 4.19 Pg, of which 2.96 Pg is locked in the soil (Hamilton and Friess, 2018). They are among the forests with the highest carbon storage in the soil on the planet at the Millennium scale (Atwood et al., 2017; Choi and Wang, 2004; Donato et al., 2011; Maher et al., 2017). Although mangroves cover only 0.5% of the global coastal area, the carbon stored in the mangrove soils, 24 Tg/a, accounts for 10%–15% of the carbon preserved in coastal sediments (Alongi, 2014). Recent evidences further indicate that considerable amounts of the carbon, equivalent to 30%–40% of the global riverine organic carbon flux, that should have been buried in the soil have been lost (Hamilton and Friess, 2018; Bouillon et al., 2008). One invisible pathway of the soil carbon exported to the coastal water is via pore water exchange and/or submarine groundwater discharge with a potential loss rate 40% as high as the annual primary production of mangroves (Alongi, 2014). The transport efficiency of this pathway is affected by sediment properties such as particle size and permeability (Konikow et al., 2013; Robinson et al., 2007). Mangrove sediments are mostly silty clay up to 5–7 m deep with low permeability and strong viscosity, so the discharge of fresh groundwater is generally hindered (Whelan et al., 2005). In mangroves, therefore, pore water exchange is the main pathway of material exchange between the sediment and tidal creek water.
The pore water exchange in mangroves has been described as a mangrove pump (Tait et al., 2016). At high tides, the water from tidal creeks enters the pores densely distributed in the soils due to pressure gradients, and flows out at low tides, carrying large amounts of dissolved substances, such as dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), and nutrients, into the tidal creeks (Maher et al., 2013; Santos et al., 2019; Reithmaier et al., 2021). Recent studies have shown that about 5.6 Tg of soil carbon in global mangrove systems has been laterally exported into nearshore waters every year, 75%–80% of which is discharged in the form of DIC (Alongi, 2014, 2020; Chen et al., 2018; Ray et al., 2018), which explains why mangrove tidal creeks are shown to be a main source of atmospheric CO2 (Santos et al., 2012; Chen et al., 2021b).
Invasion of S. alterniflora along the Chinese coast has become a widespread environmental concern from the Bohai Sea southward to Hainan Island over the past few decades (Chen, 2021). For example, in the Zhangjiang River Estuary, the areal extent of S. alterniflora in the native mangrove system had doubled during 2003–2015 (Liu et al., 2017), thus forming an ecotone of mangrove-S. alterniflora. Previous studies have advanced our understanding of the impact of pore water input in mangrove tidal creeks on the carbon cycle (Kristensen et al., 2008; Call et al., 2019), but pore water exchange and related carbon cycle still remain relatively understudied on ecotone formed under the invasion of S. alterniflora. Does the carbon flux via pore water exchange in the Spartina-dominated area differ from the mangrove-dominated area? What is the subsequent fate of the dissolved carbon exported from the soil to the creeks via pore water exchange in both areas?
In order to explore the fate of carbon exported via pore water exchange and to compare the mangrove-dominated system with the Spartina-dominated system, we have utilized radium and radon as pore water tracers to calculate the DIC and DOC fluxes via pore water exchange in the subtropical mangrove-S. alterniflora ecotone in the Zhangjiang River Estuary.
The Zhangjiang River Estuary Mangrove National Nature Reserve is located in the subtropical Zhangjiang River Estuary in Fujian Province, China (23.91°−23.93°N, 117.41°−117.43°E) (Fig. 1). The whole terrain descends from northwest to southeast, forming a horseshoe-shaped landform opening to the southeast. Many creeks are distributed in the mangrove forest, and finally converge with the main stream of the Zhangjiang River before flowing into the Dongshan Bay and further into the Taiwan Strait (Zhang et al., 2013). This area is influenced by the East Asian monsoons, with annual average temperature of 21.2℃, wind speed of 2.7 m/h, and precipitation of 1 715 mm (Gao et al., 2018). The creeks are affected by irregular semi-diurnal tides with a range of 0.43–4.67 m and an average of 2.32 m (Chen et al., 2010b; Hui et al., 2006). Some coastal vegetations are submerged during flood tides, and large areas of mudflats are exposed at ebb tides (Chen et al., 2010b). The dominant species of mangroves in the Zhangjiang River Estuary are Kandeliaobovata, Aegiceras corniculatum, and Avicennia marina (Feng et al., 2017). The mangrove roots usually develop within 90 cm of the ground surface (Lin, 2019). They play an important role in preventing soil erosion and storing buried carbon in the soil. However, the mangrove soils are mainly composed of silty clay with thickness of more than 2 m (Li et al., 2018), so the roots of these mangroves cannot penetrate the low permeability soil layer so as for terrestrial groundwater in the deep aquifer to upwell. Exchanges between the soil and creek waters are mainly via densely distributed biological pores in the soil (Ridd, 1996).
Field observations were conducted during September 2–4, 2018 (wet season) and March 9–11, 2019 (dry season) in the mangrove-Spartina ecotone of Zhangjiang River Estuary (Fig. 1b). Time-series observations were carried out in tidal creeks at Station TS1 (23.927 2°N, 117.417 2°E) in the mangrove-dominated area in both seasons and at Station TS2 (23.922 2°N, 117.423 1°E), which is at the edge of the mangrove forest with serious invasion of S. alterniflora and about 400 m away from Station TS1, in the dry season (Figs 1c-e). Unlike Station TS1 where the coast was covered by mangroves, Station TS2 had a coast of exposed mudflats where S. alterniflora invaded. Hydrographic parameters, temperature, water depth, and salinity were determined with Aqua TROLL 200 (In-Situ Inc., USA). The meteorological parameters, wind speed and air pressure were measured with an automatic weather station (R.M. YOUNG, USA). Water samples were taken for 222Rn, 226Ra, 228Ra, DIC, total alkalinity (TA) and DOC every 2 h for 24 h at the two stations using a glass water sampler. In addition, we sampled the Zhangjiang River water, seawater, pore water, and well water for the same parameters during the same period. Water samples from the Zhangjiang River, seawater, and domestic wells were collected in the same way as the tidal creek water. Pore water samples were collected during the ebb tide by digging bores to a depth of about 50 cm and waiting for the water to converge naturally at the edge of the tidal creek in the mangroves. The water in each bore was purged at least three times before sample collection. We used a WTW Multi 340i to measure the temperature and salinity of water samples after each collection. Unfortunately, at Station TS2 we failed to measure the partial pressure of carbon dioxide (pCO2) due to equipment failure. The pCO2 value was calculated using CO2SYS (Pelletier et al., 2015) using measured DIC, TA, salinity and temperature. As the weather station was damaged at Station TS2, the average values of wind speed and air pressure at Station TS1 on the same day were used. 222Rn samples were collected in 250 mL bottles and the activity of 222Rn was determined with RAD7 (Durridge Co., USA) using Water 250 protocol right after sampling. In addition, sediment cores were collected with 65 mm-diameter PVC pipes to estimate diffusive fluxes of 222Rn across the sediment-water interface using a sediment equilibration method detailed in Corbett et al. (1998). A Rhizon sampling system (the Netherlands) was used to collect pore water in the cores as detailed in Seeberg-Elverfeldt et al. (2005). We used PICARRO G2101-i and PICARRO G2132-i (USA) to measure pCO2 in situ.
In the field, water samples for 226Ra and 228Ra were enriched for radium with 16 g of MnO2-coated fibers (Mn-fibers) at a flow rate of less than 0.6 L/min immediately after collection following the procedure in Moore and Arnold (1996). The Mn-fibers were washed with deionized water to remove the salt and particles. DIC and TA samples were collected in 250 mL borosilicate glass bottles and preserved with saturated HgCl2. For DOC, samples were collected in 40 mL dark glass bottles after filtration through a syringe filter assembled with a pre-burned (450℃ for 5 h) GF/F membrane, then preserved with H3PO4 before being kept at −20℃ until further analysis.
The radium adsorbed on the Mn-fiber was leached with a mixture of 1 mol/L hydroxylamine hydrochloride and 1 mol/L HCl at a ratio of 2:1 at 80℃. Then, saturated Ba(NO3)2 and 1 mol/L NaHSO4 were added to the solution to co-precipitate radium with BaSO4. The precipitate was stored for 21 d before being measured with a germanium gamma detector (GCW4022, Canberra, Germany). The measurement error of 226Ra and 228Ra was less than 5%.
DIC and TA samples were equilibrated at 25℃ before measurements. The concentration of DIC was measured using a DIC analyser (Apollo, USA). The concentration of TA was determined using an automatic alkalinity titrator (Apollo, USA). Both determinations of DIC and TA were corrected with reference seawater (provided by Andrew Dickson, the Scripps Institution of Oceanography, USA), and the measurement errors were less than 0.1%.
For DOC, the refrigerated samples were first thawed at a laboratory temperature and then analyzed using a total organic carbon (TOC) analyzer (Shimadzu TOC-V CPH, Japan). Certified reference materials (from Hansell Laboratory at University of Miami) were used for DOC quality control.
In this study, in order to ensure the reliability of our results, two radioactive tracers, 222Rn and 228Ra, were collected to estimate the pore water exchange rate for comparison. Similar to the 222Rn mass balance model established by Chen et al. (2018), we established a mass balance model of 228Ra for comparison.
The sources of 222Rn in the tidal creeks include the river, pore water exchange, sediment diffusion, and the ingrowth from 226Ra. The sinks are decay, atmospheric evasion, tidal effects, and mixing with the seawater. At each time-series station, the mass balance model of 222Rn is as follows (Chen et al., 2018):
| $$ {F}_{\rm{R}1}+{F}_{\rm{PW}1}+{F}_{\rm{S}1}+{F}_{\rm{Ra}}+{F}_{\rm{in}1}-{F}_{\rm{out}1}-{F}_{\rm{A}}-{F}_{\rm{D}}-{F}_{\rm{M}1}={\Delta F}_{1} , $$ | (1) |
in which
| $$ {\Delta F}_{1}=\frac{{I}_{t+\Delta t}-{I}_{t}}{\Delta t} , $$ | (2) |
where FR1 and FPW1 are the flux of 222Rn attributed by the river and pore water exchange; FS1 is diffusion flux from the sediment; and FRa is the ingrowth from 226Ra. Fin1 and Fout1 are the influx and outflux due to tides, respectively. FA is the atmospheric evasion flux; FD is the decay of radon; FM1 is the flux due to mixing with the seawater; and
The monthly average discharge of the Zhangjiang River in March and September of 2019 is 20.8 m3/s and 21.7 m3/s, respectively. FR1 can be obtained by the river discharge multiplied by the 222Rn concentration of the river endmember.
The tidal influx and outflux (Zhang et al., 2016) can be calculated as
| $$ {F}_{\rm{in}1}=\frac{{h}_{t+\Delta t}-{h}_{t}}{\Delta t}(b{\overline{C}}_{\rm{creek}}+\left(1-b\right){C}_{\rm{SW}}) , $$ | (3) |
| $$ {F}_{\rm{out}1}=\frac{{h}_{t}{-h}_{t+\Delta t}}{\Delta t} {C}_{\rm{creek}} , $$ | (4) |
where h is the water depth,
| $$ {f}_{\mathrm{R}}+{f}_{\mathrm{P}\mathrm{W}}+{f}_{\mathrm{S}\mathrm{W}}=1 , $$ | (5) |
| $$ {S}_{\mathrm{R}}{f}_{\mathrm{R}}+{S}_{\mathrm{P}\mathrm{W}}{f}_{\mathrm{P}\mathrm{W}}+{S}_{\mathrm{S}\mathrm{W}}{f}_{\mathrm{S}\mathrm{W}}={S}_{\mathrm{M}} , $$ | (6) |
| $$ {}^{228}{{\rm{Ra}}_{\rm{R}}f}_{\rm{R}}+{{}^{228}{\rm{Ra}}}_{\rm{PW}}{f}_{\rm{PW}}+{{}^{228}\mathrm{Ra}}_{\rm{SW}}{f}_{\rm{SW}}={{}^{228}\mathrm{Ra}}_{\rm{M}} , $$ | (7) |
where fR, fPW and fSW are the fraction of river water, pore water, and seawater endmembers; SR, SPW and SSW are the salinity of river water, pore water, and seawater endmembers;
The supported flux of 222Rn by 226Ra decay (FRa) and the decay of 222Rn (FD) are as follows:
| $$ {F}_{\mathrm{Ra}}={ \text{λ} }_{\mathrm{Rn}}\times {C}_{\mathrm{Ra}}\times h\ , $$ | (8) |
| $$ {F}_{\mathrm{D}}={ \text{λ} }_{\mathrm{R}\mathrm{n}}\times [{C}_{\mathrm{creek}}\times \left(1-{\mathrm{e}}^{-{ \text{λ} }_{\mathrm{R}\mathrm{n}}\Delta t}\right)] , $$ | (9) |
where
The diffusion flux (Martens et al., 1980; Peng et al., 1974) was calculated as
| $$ {F}_{\mathrm{S}1}={\left({ \text{λ}}_{\mathrm{R}\mathrm{n}}\times \phi \times {D}_{\mathrm{m}}\right)}^{0.5}\times ({C}_{\mathrm{e}\mathrm{q}}-{C}_{\mathrm{c}\mathrm{r}\mathrm{e}\mathrm{e}\mathrm{k}}) , $$ | (10) |
| $$ {D}_{\mathrm{m}}={10}^{-\left(\frac{980}{T+273}+1.59\right)} , $$ | (11) |
where
The atmospheric flux (MacIntyre et al., 1995) was calculated as
| $$ {F}_{\mathrm{A}}={k}_{1}({C}_{\mathrm{creek}}-\alpha {C}_{\rm{air}}) , $$ | (12) |
where
| $$ \alpha =0.105+0.405{\rm{e}}^{-0.050\; 2T} . $$ | (13) |
The gas transfer velocity was determined with wind speed (Lambert and Burnett, 2003):
| $$ {k}_{1}=0.45{u}^{1.6}\times {\left(\frac{{S}_{{\mathrm{C}}_{1}}}{600}\right)}^{-X} , $$ | (14) |
where u is the wind speed, when u < 3.6 m/s, X = 0.666 7, and when u > 3.6 m/s, X = 0.5.
| $$ {S}_{{\mathrm{C}}_{1}}={\frac{\nu}{{A\times \mathrm{e}}^{\left(-\frac{E}{RT}\right)}}}, $$ | (15) |
where ν is the kinematic viscosity (m2/s), A (in 10−9 m2/s) and E (the energy of activation of diffusion, J/mol) are fitting parameters, and R is the gas constant (8.314 5 J/(mol∙K)).
The mixing loss was estimated by the net 222Rn flux after corrections for tidal effect, 226Ra ingrowth, sediment diffusion, the decay of 222Rn, and atmospheric loss. The net 222Rn flux is described as follows (Zhang et al., 2016):
| $$ {F}_{\mathrm{net}}={\Delta F}_{1}-{F}_{\mathrm{R}\mathrm{a}}-{F}_{\mathrm{in}1}-{F}_{\mathrm{R}1}-{F}_{\mathrm{S}1}+{F}_{\mathrm{out}1}+{F}_{\mathrm{A}}+{F}_{\mathrm{D}} . $$ | (16) |
We chose the maximum negative Fnet as a conservative estimate of FM (mixing loss) as suggested by Burnett and Dulaiova (2003). Fnet should be a balance between FPW and FM. So, the 222Rn flux contributed by pore water is
| $$ {F}_{\mathrm{P}\mathrm{W}1}={F}_{\mathrm{n}\mathrm{e}\mathrm{t}}+{F}_{\mathrm{M}1} . $$ | (17) |
We used the conservative estimate of FM to calculate the minimum FPW. The rate of pore water exchange (ω, cm/s) was obtained by FPW divided by the 222Rn concentration in the pore water endmember (CPW):
| $$ \omega =\frac{{F}_{\rm{PW}1}}{{C}_{\rm{PW}}} . $$ | (18) |
228Ra has no atmospheric evasion, but desorption from particles has to be taken into account. The half-life of 228Ra is 5.75 a, so that its decay can be ignored in a tidal cycle. Similar to 222Rn, a mass balance model of 228Ra was set up as following to estimate the rate of pore water exchange:
| $$ {F}_{\mathrm{R}2}+{F}_{\mathrm{P}\mathrm{W}2}+{F}_{\mathrm{S}2}+{F}_{\mathrm{P}}+{F}_{\mathrm{i}\mathrm{n}2}-{F}_{\mathrm{o}\mathrm{u}\mathrm{t}2}-{F}_{\mathrm{M}2}={\Delta F}_{2} , $$ | (19) |
where FR2 and FPW2 are the flux of 228Ra attributed by the river and pore water exchange; Fin2 and Fout2 are the influx and outflux due to tides, respectively; FM2 is the flux due to mixing with the seawater; and
The net carbon flux via pore water exchange into the tidal creeks was estimated using the average 222Rn-based advection rate multiplied by the difference between the concentrations of dissolved carbon in the pore water and in the tidal creeks.
The flux of air-water CO2 (
| $$ {F}_{{\rm{CO}}_{2}}={K}_{{h}}\times {k}_{2}\times \Delta p{\rm{CO}}_{2} , $$ | (20) |
where Kh is the solubility coefficient, calculated following Weiss (1974):
| $$ {K}_{h}={{\rm{e}}}^{A1+A2\left(\frac{100}{T}\right)+A3\;\mathrm{ln}\left(\frac{T}{100}\right)+S\left[B1+B2\left(\frac{T}{100}\right)+B3{\left(\frac{T}{100}\right)}^{2}\right]} , $$ | (21) |
where A and B are constants, the unit is in mol/(kg∙atm) (1 atm = 101 325 Pa). T is absolute temperature and S is salinity. A1 = −60.240 9, A2 = 93.451 7, A3 = 23.358 5, B1 = 0.023 517, B2 = −0.023 656 and B3 = 0.004 736.
| $$ {k}_{2}=0.27{u}^{2}\times {\left(\frac{{S}_{{\mathrm{C}}_{2}}}{600}\right)}^{-X} , $$ | (22) |
where u is the wind speed, when u < 3.6 m/s, X = 0.666 7, and when u > 3.6 m/s, X = 0.5.
To determine the emission of CO2 from the creeks contributed by pore water exchange, we calculated the pCO2 resulting from pore water exchange in the creek based on the mass balance of DIC and TA in the creeks. Firstly, the concentration of DIC without the contribution of pore water exchange was designated as DIC0 and was estimated as follows. The DIC inventory in the creek was obtained by
| $$ {I}_{\mathrm{C}}={C}_{\mathrm{C}}\times V , $$ | (23) |
where IC is the inventory of DIC in the creek; CC is the DIC concentration in the creek; and V is the volume of water in the creek. The inventory of DIC contributed by seawater (ISW) was calculated as
| $$ {I}_{\mathrm{S}\mathrm{W}}=V\times {C}_{\mathrm{S}\mathrm{W}}\times b , $$ | (24) |
where CSW is the DIC concentration of the seawater endmember. Since the total DIC inventory in the study area was mainly contributed by seawater, pore water exchange, river water and sediments, the contribution of pore water exchange, river water and sediments to the total inventory can be obtained by subtracting the contribution of seawater from the total DIC inventory. The inventory of DIC contributed by pore water exchange (IPW) was thus calculated as
| $$ {I}_{\rm{PW}}=\frac{{F}_{\rm{PW}}}{{F}_{\rm{PW}}+{F}_{\rm{S}}+{F}_{\rm{R}}}({I}_{\rm{C}}-{I}_{\rm{SW}}) , $$ | (25) |
where FPW, FS, and FR denote the flux of DIC associated with pore water exchange, sediment, and the Zhangjiang River, respectively. The concentration of DIC without the contribution of pore water exchange (DIC0) was calculated as
| $$ {\mathrm{D}\mathrm{I}\mathrm{C}}_{0}=\frac{{I}_{\mathrm{C}}-{I}_{\mathrm{P}\mathrm{W}}}{V} . $$ | (26) |
Similarly, the concentration of TA without the contribution of pore water exchange (TA0) was obtained. Secondly, the pCO2 in the creek without pore water exchange contribution (
| $$ {F}_{\mathrm{C}{\mathrm{O}}_{{2}_{\mathrm{P}\mathrm{W}}}}={F}_{\mathrm{C}{\mathrm{O}}_{2}}-{F}_{\mathrm{C}{\mathrm{O}}_{{2}_{0}}} . $$ | (27) |
The salinity in the pore water around the ecozone ranged from 9.6 to 13.2 with an average of (11.7 ± 1.2) in the wet season, while it changed from 17.3 to 22.8 with an average of (21.4 ± 2.0) in the dry season (Table 1). The activities of pore water 222Rn and 228Ra varied greatly downstream along the coast of the mangrove creek in both seasons, from 1 240−4 630 Bq/m3 with an average of (2 670 ± 1 290) Bq/m3 for 222Rn and from 489−1 225 dpm/(100 L) with an average of (797 ± 245) dpm/(100 L) for 228Ra in the wet season, while from 1 410−5 130 Bq/m3 with an average of (3 080 ± 1 350) Bq/m3 for 222Rn and from 651−1 143 with an average of (744 ± 303) dpm/(100 L) for 228Ra in the dry season. The activity ratio of 228Ra to 226Ra, (228Ra/226Ra)AR of the pore water was (4.66 ± 1.94) in the wet season and slightly higher in the dry season (5.71 ± 0.71) (Fig. 2). On average, the pore water had a DIC concentration of (3 970 ± 1 400) µmol/L in the wet season and a few percents greater in the dry season. The concentration of DOC (µmol/L) was in the range from 206 to 425 with an average of (308 ± 65) in the wet season, and its average varied within 1% in the dry season. The properties of well water (fresh groundwater) were quite different from those of pore water. The activity of 222Rn was much greater in both seasons, about 20−30 times as much as that of pore water. However, the activity of 228Ra was only 7% equivalent to that of pore water. And the difference in (228Ra/226Ra)AR between the pore water and well water was also obvious. The (228Ra/226Ra)AR of the well water was (0.49 ± 0.22) and (0.65 ± 0.28) in the wet and dry seasons, respectively, which were much lower than that of the pore water (Fig. 2). In terms of the composition of dissolved carbon, the well water had a DIC concentration similar to the pore water, (4 098 ± 3 021) µmol/L in the wet season and (3 650 ± 611) µmol/L in the dry season, while its DOC concentration was an order of magnitude smaller than in the pore water in both seasons. The concentration of dissolved carbon of the Zhangjiang River water was the lowest in the carbon sources of the tidal creek, 628 µmol/L for DIC and 160 µmol/L for DOC in the dry season and about 100 µmol/L lower for DIC and 10 µmol/L lower for DOC in the wet season. The activities of 222Rn and 228Ra of the river water, 880 Bq/m3 and 41 dpm/(100 L) in the wet season and 610 Bq/m3 and 29 dpm/(100 L) in the dry season, were much lower than in the pore water. The value of (228Ra/226Ra)AR of the Zhangjiang River water was (1.41 ± 0.07) in the wet season and (1.49 ± 0.05) in the dry season. The seawater endmember had the lowest 222Rn activity concentration, 77 Bq/m3, in the wet season and remained the same order of magnitude in the dry season. The activity of 228Ra in the seawater varied from 181 dpm/(100 L) in the wet season to 154 dpm/(100 L) in the dry season. The concentration of DIC of the seawater endmember was a few times greater than in the river water, while the concentration of DOC was almost the same as in the river water (Table 1).
| Season | ID | Latitude | Longitude | Depth/m | Salinity | 222Rn/ (Bq∙m−3) | 226Ra/ (dpm∙(100 L)−1) | 228Ra/ (dpm∙(100 L)−1) | DIC/ (μmol∙L−1) | TA/ (μmol∙L−1) | DOC (μmol∙L−1) |
| Wet season | PW 1 | 23.9270°N | 117.4174°E | 0.5 | 12.7 | 3070 | 203 | 802 | 5355 | 4061 | 359 |
| PW 2 | 23.9270°N | 117.4174°E | 0.5 | 12.0 | 3070 | 193 | 847 | 6169 | 4336 | 343 | |
| PW 3 | 23.9261°N | 117.4164°E | 0.5 | 11.0 | 2210 | 176 | 750 | 3050 | 2605 | 258 | |
| PW 4 | 23.9259°N | 117.4186°E | 0.5 | 12.4 | 4630 | 154 | 1024 | 4023 | 3382 | 425 | |
| PW 5 | 23.9253°N | 117.4186°E | 0.5 | 11.0 | 1240 | 154 | 934 | 2784 | 2519 | 254 | |
| PW 6 | 23.9222°N | 117.4233°E | 0.5 | 13.2 | 1280 | 192 | 1225 | 4252 | 3916 | 323 | |
| PW 7 | 23.9158°N | 117.4308°E | 0.5 | 9.6 | 2350 | 99 | 501 | 2579 | 2383 | 315 | |
| PW 8 | 23.9317°N | 117.4335°E | 0.5 | 12.7 | 4600 | 118 | 489 | 5271 | 4706 | 288 | |
| PW 10 | 23.9253°N | 117.4294°E | 0.5 | 11.0 | 1620 | 145 | 600 | 2246 | 2129 | 206 | |
| Well 1 | 23.9247°N | 117.4109°E | 0 | 1.1 | 139000 | 81 | 67 | 6306 | 4173 | 46 | |
| Well 2 | 23.9204°N | 117.4138°E | 0 | 0.0 | 36700 | 55 | 38 | 1891 | 1168 | 11 | |
| SED 3 | 23.9261°N | 117.4150°E | 0.1 | − | 1280 | − | − | − | − | − | |
| SED 4 | 23.9261°N | 117.4164°E | 0.1 | − | 550 | − | − | − | − | − | |
| SED 6 | 23.9253°N | 117.4186°E | 0.1 | − | 543 | − | − | − | − | − | |
| SED 7 | 23.9222°N | 117.4233°E | 0.1 | − | 170 | − | − | − | − | − | |
| SED 10 | 23.9253°N | 117.4294°E | 0.1 | − | 543 | − | − | − | − | − | |
| ZJ | 23.9528°N | 117.3613°E | 0 | 0.0 | 880 | 29 | 41 | 518 | 392 | 149 | |
| SW | 23.9147°N | 117.4706°E | 0 | 20.1 | 77 | 63 | 181 | 1528 | 1623 | 154 | |
| Dry season | PW 1 | 23.9270°N | 117.4174°E | 0.5 | 17.3 | 4030 | 145 | 676 | 3061 | 2030 | 187 |
| PW 3 | 23.9270°N | 117.4164°E | 0.5 | 22.0 | 1410 | 189 | 1005 | 3336 | 3104 | 465 | |
| PW 4 | 23.9261°N | 117.4186°E | 0.5 | 20.3 | 3830 | 147 | 677 | 5296 | 4767 | 322 | |
| PW 6 | 23.9259°N | 117.4233°E | 0.5 | 22.4 | 1580 | 224 | 1143 | 3507 | 3027 | 214 | |
| PW 7 | 23.9253°N | 117.4308°E | 0.5 | 22.8 | 2980 | 122 | 651 | 3121 | 2756 | 384 | |
| PW 8 | 23.9222°N | 117.4335°E | 0.5 | 22.3 | 5130 | 166 | 853 | 7577°N | 7128°E | 300 | |
| PW 10 | 23.9158°N | 117.4294°E | 0.5 | 22.6 | 2630 | 58 | 203 | 3033 | 2749 | 262 | |
| Well 1 | 23.9317°N | 117.4109°E | 0 | 0.9 | 111000 | 77 | 78 | 6775 | 3766 | 62 | |
| Well 2 | 23.9253°N | 117.4138°E | 0 | 0.0 | 37700 | 25 | 30 | 2138 | 1139 | 77 | |
| Well 3 | 23.9242°N | 117.4128°E | 0 | 0.0 | 33100 | 22 | 34 | 4205 | 2716 | 54 | |
| Well 4 | 23.9242°N | 117.4136°E | 0 | 0.0 | 112000 | 69 | 46 | 3116 | 1803 | 39 | |
| SED 3 | 23.9247°N | 117.4150°E | 0.1 | − | 737 | − | − | − | − | − | |
| SED 4 | 23.9204°N | 117.4164°E | 0.1 | − | 0 | − | − | − | − | − | |
| SED 5 | 23.9261°N | 117.4186°E | 0.1 | − | 373 | − | − | − | − | − | |
| SED 6 | 23.9261°N | 117.4233°E | 0.1 | − | 377 | − | − | − | − | − | |
| SED 7 | 23.9253°N | 117.4294°E | 0.1 | − | 373 | − | − | − | − | − | |
| SED 9 | 23.9158°N | 117.4308°E | 0.1 | − | 547 | − | − | − | − | − | |
| ZJ | 23.9528°N | 117.3613°E | 0 | 0.0 | 610 | 19 | 29 | 628 | 658 | 160 | |
| SW | 23.9147°N | 117.4706°E | 0 | 26.2 | 127 | 36 | 154 | 1939 | 2046 | 141 | |
| Note: PW represents pore water; Well, well water; SED, the interstitial water of sediments; ZJ, the Zhangjiang River endmember; and SW, the seawater endmember; DIC, dissolved inorganic concentration; DOC, dissolved organic concentration; TA, total alkalinity. 222Rn, 226Ra and 228Ra parameters indicate their activity concentrations. − represents no data. | |||||||||||
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During the 24-h observations at Station TS1, the tidal ranges in the wet season and the dry season were 2.5 m and 2.3 m, respectively. The salinity ranged from 2.0 to 8.2 in the wet season with no obvious pattern with water depth (Fig. 3a). In contrast, salinity varied in a greater range of 1.9−11.2 with a pattern more consistent with the variation of water depth in the dry season (Fig. 3b). The diurnal variation in temperature was greater in the wet season (25.2−35.3℃) than in the dry season (16.0−18.0℃). The activity of 222Rn dropped sharply during the flood tide from 797 Bq/m3 to 283 Bq/m3 and increased from 283 Bq/m3 to 437 Bq/m3 during the ebb tide in the wet season (Fig. 3a), whereas in the dry season it decreased from 603 Bq/m3 to 320 Bq/m3 during the flood flow and increased from 320 Bq/m3 to 827 Bq/m3 during the ebb flow (Fig. 3b).
Similar to the tidal pattern of 222Rn, the activity of 228Ra also mirrored the water depth varying from 91 dpm/(100 L) to 284 dpm/(100 L) in the wet season (Fig. 3a). The (228Ra/226Ra)AR in the mangrove-dominated creek in the wet season, (6.97 ± 0.54), was significantly higher than that of the well water, (0.49 ± 0.22), but similar to that of the pore water, (4.66 ± 1.94) (Fig. 2a). The tidal fluctuations of DIC and DOC concentrations showed trends similar to 222Rn and 228Ra in the wet season, with maximum DIC and DOC of 2 044 μmol/L and 468 μmol/L at the tidal trough and minimum DIC and DOC of 923 μmol/L and 247 μmol/L at the tidal crest (Fig. 3a). In the dry season, the concentrations of DIC and DOC followed similar tidal patterns with smaller diurnal variations, from 1 099−1 539 μmol/L for DIC and from 276−698 μmol/L for DOC (Fig. 3b). Meanwhile, pCO2 reached a peak value of 6 075 µatm at the lowest tide and a minimum value of 1 822 µatm at the highest tide in the wet season (Fig. 3a). In the dry season, the diel variation in pCO2 was relatively small from 1 878−4 940 µatm. The atmospheric pCO2 in the dry and wet seasons were 412 µatm and 388 µatm, respectively. Therefore, pCO2 in the creek far exceeded the atmospheric value in both wet and dry seasons, indicating that the tidal creek in the mangrove-dominated area was a strong source of atmospheric CO2. The average air pressure during September 2−4, 2018 was 100.5 kPa, while the average air pressure during March 9−11, 2019 was 101.1 kPa. The
The diurnal variation in salinity at Station TS2 was from 1.3−9.3, which followed a pattern consistent with that in water depth, while the temperature with a diel range from 17.1℃ to 18.3℃ had no apparent trend. The activities of 222Rn and 228Ra varied with the same tidal pattern of decreasing with water depth. The diurnal change was from 227−760 Bq/m3 in 222Rn and 75−160 dpm/(100 L) in 228Ra (Fig. 3c). The (228Ra/226Ra)AR in the Spartina-dominated creek in the dry season, (5.27 ± 0.56), was significantly higher than that of the well water, (0.65 ± 0.28), but almost the same as that of the pore water, (5.71 ± 0.71) (Fig. 2b). The diel pattern of dissolved carbon was similar to that at Station TS1, with DIC in the range of 1 067−1 853 µmol/L and DOC in the range of 229−490 µmol/L (Fig. 3c). The diurnal variation in DIC at Station TS2 was 786 μmol/L, greater than its variation at Station TS1, while the diurnal change in DOC was 261 μmol/L. The
The flux of 228Ra from desorption from suspended particles was equivalent to 1% of that of rivers, 1%−3% of that of seawater, and less than 1% of that of pore water exchange. Therefore, the contribution from particle desorption can be ignored in the endmember mixing model. According to the distributions of 228Ra and salinity in the tidal creeks, three endmembers, seawater, the Zhangjiang River, and pore water were identified (Fig. 4). The proportion of seawater, i.e., the return flow factor, ranged from 2.7% to 28.9% in the mangrove-dominated creek in the wet season, and 0.3% to 33.8% in the Spartina-dominated creek in the dry season.
In the mangrove-dominated creek (Station TS1), the pore water exchange rate in the wet season using the two tracers, 228Ra and 222Rn, was similar. The 222Rn-rate was [0, (9.0 ± 1.1)] cm/h with an integration rate over the observation period (24 h) of (82.1 ± 27.3) cm/d and the 228Ra-rate was [0, (9.2 ± 0.9)] cm/h with an integration rate of (77.4 ± 30.1) cm/d. The similarity of the two rates confirms the reliability of our calculations. Since the collection and determination of 222Rn are relatively convenient, our subsequent rate estimation in the dry season was based on 222Rn, which was [0, (13.6 ± 2.1)] cm/h with an integration rate of (110.0 ± 21.5) cm/d at Station TS1 and [0, (11.9 ± 2.1)] cm/h with an integration rate of (93.3 ± 50.2) cm/d in the Spartina-dominated creek (Station TS2). The rate fluctuated with the tide, with the minimum mostly occurring either at the tidal crest or the tidal trough in each tidal cycle (Fig. 5). Our pore water exchange rates are three orders of magnitude higher than that calculated by Wang et al. (2022). This discrepancy between our results and Wang et al. (2022) is caused by potentially great spatial differences in pore water exchange rates, different locations of sampling, and different methodology. Wang et al. (2022) adopted a direct observation of the change of water volume in two sediment pores with time to estimate the pore water exchange rate, one sediment pore was located in the salt marshes and the other was in the mangrove forest. In our study, we adopted an indirect method using radium and radon as the pore water exchange tracers to estimate the rate based on the changes of the tracers with time in the tidal creek. Apparently, the tidal creek received greater amount of pore water from surrounding pores in which many had much greater pore water exchange than those in Wang et al. (2022).
In the mangrove-dominated creek, the pore water exchange rate, (0.82 ± 0.27) m/d, was used to estimate the associated carbon flux in the wet season and (1.10 ± 0.22) m/d was used in the dry season. The associated carbon flux was (2.16 ± 0.63) mol/(m2∙d) for DIC and (–0.008 ± 0.07) mol/(m2∙d) for DOC in the wet season and (3.02 ± 0.65) mol/(m2∙d) for DIC and (−0.15 ± 0.007) mol/(m2∙d) for DOC in the dry season. The negative value means that pore water was a sink of DOC in the creek. The dissolved carbon (DC, the sum of DIC and DOC) flux via pore water exchange was (2.15 ± 0.63) mol/(m2∙d) in the wet season and (2.87 ± 0.65) mol/(m2∙d) in the dry season. In the S. alterniflora-dominated creek, using the pore water exchange rate of (0.93 ± 0.50) cm/d, less DIC, (2.52 ± 0.82) mol/(m2∙d), and DOC, (0.02 ± 0.09) mol/(m2∙d), inputs from the pore water occurred in the dry season, which resulted in a DC flux of (2.54 ± 0.82) mol/(m2∙d). The DC flux via pore water exchange was about 6−8 times greater than the riverine input in both seasons in the creeks of the mangrove-S. alterniflora ecozone (Fig. 6), indicating that pore water exchange was a much more important carbon source than the river.
The DIC flux via pore water exchange in the dry season was higher than in the wet season in the mangrove creek. This seasonal pattern differs from that in tropical Maowei Sea, where the estimated DIC flux was greater in the wet season as higher temperatures in the wet season, which can increase the activities of microbes to degrade more organic matter in mangrove soils and release larger amounts of DIC into aquifers (Chen et al., 2018). The reason for this difference is that the DIC flux via pore water exchange is determined not only by the concentration of the pore water endmember, but also by the pore water exchange rate. Although the DIC concentration of the pore water endmember in our system was slightly higher in the wet season (3 930 ± 1 410) than in the dry season (3 559 ± 870), the pore water exchange rate was higher in the dry season than in the wet season. The greater DIC flux via pore water exchange in the dry season in our system indicates that its seasonality was controlled more by the pore water exchange rate. Similarly, the DC flux was greater in the dry season than in the wet season.
The uncertainty in the pore water exchange rate was caused by the uncertainty in every other parameter in Eqs (1)−(18). Diffusion from sediments was taken as constant, so its contribution to the uncertainty in the pore water exchange rate was not evaluated. Here the uncertainties in h, t, λRn, T, and μ were taken as 0. The uncertainties in salinity, 222Rn, 228Ra, and carbon concentrations of the pore water endmember were the standard deviations of these parameters at multiple sites. Since there was only one sampling site for both the river water and sea water, the uncertainties of the above parameters of the river water and sea water were the measurement errors. Using error propagation (Text S1), the total uncertainty in the pore water exchange rate was mainly contributed by the uncertainty of 222Rn and 228Ra in the pore water endmember and the creek water (Table S2). For the radon-derived pore water exchange rate, the measurement error of radon was the largest source of uncertainty, while for the radium-derived pore water exchange rate, the largest uncertainty resulted from the spatial variation in the activity of 228Ra in the pore water endmember. The daily pore water exchange rate is the result of integrating the pore water exchange rate over the observation period (24 h), so the uncertainty of the daily rate we reported is the error propagated from the uncertainties of the discrete pore water exchange rates used in the integration.
The uncertainties in the net pore water exchange DIC and DOC fluxes resulted mainly from the uncertainty in the pore water exchange rate and the uncertainty in the carbon concentration of the pore water endmember, which represent the temporal variation in the pore water exchange rate and the spatial variation in the carbon concentration of the pore water endmember, respectively (Table S3). These uncertainties, however, would not change the conclusions reached based on the carbon fluxes calculated using the average chemical concentrations.
In the wet season, the average fraction of seawater, 0.13, in the mangrove-dominated creek, was taken in the calculation. In the dry season, the average return flow factor in the S. alterniflora-dominated creek, 0.15, was used for the ecozone. In the mangrove-dominated creek the pCO2 resulting from pore water exchange was 53% in the wet season and 71% in the dry season. The CO2 emission was 0−27.9 mmol/(m2∙d) (mean: (11.6 ± 8.7) mmol/(m2∙d)) in the wet season and 0.4−23.5 mmol/(m2∙d) (mean: (9.5 ± 7.4) mmol/(m2∙d)) in the dry season from the tidal creek. Pore water exchange contributed 75% of the CO2 emission in the wet season and 54% in the dry season. In the S. alterniflora-dominated creek, the CO2 emission in the dry season was 3.9−13.9 mmol/(m2∙d) (mean: (7.1 ± 2.7) mmol/(m2∙d)), 84% of which resulted from pore water exchange.
Sediments in the ecozone are mainly silty clay up to 5−7 m deep, and mangrove roots exist within 90 cm of the ground surface (Lin, 2019), so freshwater groundwater below the sediments cannot have access to the tidal creeks. Similar low permeability of mangrove sediments has prevented fresh groundwater from entering the surface water in Florida Coastal Everglades (Whelan et al., 2005; Smith et al., 2016). The exclusion of fresh groundwater in the tidal creeks was further confirmed by (228Ra/226Ra)AR at the time-series stations and in the well waters (Fig. 2). The (228Ra/226Ra)AR in coastal waters is not affected by evaporation, precipitation, and biological activities, and is only controlled by physical mixing (Chen et al., 2010a; Krest et al., 1999; Nozaki et al., 1989). 226Ra (half-life of 1 600 a) and 228Ra (half-life of 5.75 a) are long-lived radium isotopes, with their half-lives much longer than the mixing time in coastal waters so that their decay is negligible. The (228Ra/226Ra)AR in the mangrove-dominated creek in the wet season was significantly different from that of the well water, but similar to that of the pore water (Fig. 2a). In the S. alterniflora creek, a similar pattern was observed (Fig. 2b). This indicates that the creek water in the ecozone had no obvious connection with the well water, instead the pore water was a potential source of radium for the creek water. The activity of 228Ra in the creeks apparently resulted from three endmembers, the river water, pore water and seawater (Fig. 4), which supports the three-endmember mixing model.
The pore water exchange rate was 30% higher in the dry season than in the wet season in the mangrove-dominated creek. Similar seasonal patterns were observed in other mangrove areas. For example, in the Shark River in Florida, USA, a mangrove-dominated estuary, the pore water exchange rate in the dry season was about three times as much as that in the wet season (Smith et al., 2016). The greater pore water exchange rate in the dry season coincided with a lower water level at the tidal trough in both systems.
In the same season, the pore water exchange rate in the mangrove-dominated creek was about 15% greater than in the S. alterniflora-dominated creek with a greater diurnal variation (Figs 5c, d). The greater exchange rate in the mangrove-dominated creek was likely caused by the following reasons: the dominant mangrove species in the Zhangjiang River Estuary were Avicennia marina, Kandelia candel, and paulownia trees, which average height was 2.3 m and their shading degree could reach more than 90%. The growth of large plant roots of mangroves could produce more routes of water infiltration (Meek et al., 1992). In addition, the lush mangroves provided food and shelter for the fiddler crabs that dig holes in the mangroves (Stieglitz et al., 2013). Their burrows have been observed to enhance the pore water exchange capacity in the Plum Island Estuary in Massachusetts, USA (Gardner and Gaines, 2008) and on Sapelo Island in GA, USA (Koretsky et al., 2002). At mangrove margins, however, where relatively sparsely distributed S. alterniflora invaded with mudflats exposed, the vegetation coverage was much less than in the mangrove-dominated area (Feng et al., 2017) and the depth and density of caves formed by crabs decreased (Wang et al., 2014), which resulted in lower pore water exchange rate in the Spartina-dominated creek.
In terms of mangroves and salt marshes, our pore water exchange rates in the ecozone fall within the range of global pore water exchange/submairine groundwater discharge rates, 0−990 cm/d, in coastal wetlands (Susilo et al., 2005; Prakash et al., 2018; Santos et al., 2021). To take global mangrove systems, in particular, for comparison, mangroves with different coastline types were summarized (Table 2). Based on the statistics of 2016, the global mangrove area is about 1.38×105 km2, mainly distributed in the tropical area (Alongi, 2014; Chen et al., 2018), 40.5% of which is delta, 27.5% is estuary, 21.0% is open coast, and the left (11.0%) is lagoon according to the classification proposed by Worthington et al. (2020). Pore water exchange rates vary greatly in different regions, but on the whole, the rates in deltaic and estuarine mangroves are greater than those in lagoonal and open coast mangroves. The Zhangjiang River Estuary mangrove is an estuarine system, and its pore water exchange rate is at least a few time greater than that in lagoonal mangrove systems. Similar magnitude of pore water exchange was also observed in other mangrove-dominated estuaries (Table 2). Mangrove roots and biological activities, such as fiddler crabs, made densely distributed holes on both sides of the tidal creeks, which resulted in intensive pore water exchange (Stieglitz et al., 2013). These results indicate that although the low permeability of the mangrove peats prohibited fresh groundwater from entering the tidal creeks, great fluid exchange was still present due to the densely distributed burrows (Hemond and Fifield, 1982; Stieglitz et al., 2000; Wilson and Gardner, 2006; Xin et al., 2009, 2013).
| Type | Study area | PER/ (cm∙d−1) | Mean SCD/ (mg∙cm−3) | Mean CAR/ (g∙m−2 ∙a−1) | CO2 flux/ (mmol∙m−2∙d−1) | Reference |
| Delta | North Queensland, Australia | 80−990 | 29.1 ± 1.3 | 138 ± 36 | 9.4−114 | Alongi et al. (1999); Brunskill et al. (2002); Call et al. (2015); Sanders et al. (2016); Susilo et al. (2005); Tait et al. (2017) |
| Delta | northwest coast of Indonesia | − | 25.9 ± 3.2 | 426 ± 236 | 32.2−93.1 | Chen et al. (2014); Alongi (2012); Alongi et al. (2008); Donato et al. (2011); Kusumaningtyas et al. (2019); Rovai and Twilley (2021) |
| Delta | Panay Island, Philippines | − | 14.6 ± 2.9 | 214 ± 58 | − | MacKenzie et al. (2021); Thompson et al. (2014) |
| Delta | southwestern coast of the gulf, Thailand | − | 21.2 ± 1.6 | 224 ± 21 | 150 | Alongi et al. (2001); Monji et al. (2002) |
| Delta | ThanHoa, Vietnam | 4.9 | 12.5 ± 1.1 | 150 ± 30 | 34.2−155 | Grellier et al. (2017); Koné et al. (2008); Taillardat et al. (2018); Tateda et al. (2005) |
| Delta | northern Gulf of Mexico, United States | 68 | − | 450 | − | Henry and Twilley (2013); Kelly et al. (2019); Yando et al. (2016) |
| Estuary | Ceará, Brazil | 8−15 | 27.0 ± 3.1 | 651 ± 298 | 60.5−112 | Burnett et al. (2008); Pülmanns et al. (2014); Passos et al. (2016); Rovai et al. (2018); Sanders et al. (2010), Sanders et al. (2012) |
| Estuary | southeastern India | 237−747 | 15.6 ± 0.5 | − | 0.4−70.2 | Bouillon et al. (2003); Biswas et al. (2004); Prakash et al. (2018); Ranjan et al. (2011); Ray et al. (2011) |
| Estuary | Northwest Madagascar | − | 23.4 ± 3.8 | 110 | 43.6 | Arias-Ortiz et al. (2021); Borges (2003); Jones et al. (2014) |
| Estuary | Zhangjiang River Estuary, China | 82.1−110 | 15.8 | 155 | 7.1−11.6 | this study; Chen et al. (2021a) |
| Lagoon | Lagunade Terminos, Mexico | − | 49.8 ± 3.8 | 97 ± 29 | − | Adame et al. (2013); Gonneea et al. (2004); Kauffman et al. (2016); Lynch et al. (1989) |
| Lagoon | Gulf of Mexico, United States | 0.7−24.3 | 29.5 ± 5.6 | 116 ± 33 | 4.6 | Bianchi et al. (2013); Millero et al. (2001); Rovai and Twilley (2021); Rovai et al. (2018); Swarzenski et al. (2009); Yando et al. (2016) |
| Open coast | Arabian Gulf of Saudi Arabia | − | − | 19 ± 4 | − | Cusack et al. (2018) |
| Note: PER: pore water exchange rate; SCD: soil carbon density; CAR: carbon accretion rate. − represents no data. | ||||||
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As CO2 released by pore water exchange equilibrates usually within tens of seconds with bicarbonate ion in the creek water (Pilson, 2013), a simple multiplication of the pore water exchange rate and the CO2 concentration in the pore water is not what the pore water exchange really contributes to the air-sea CO2 flux. How much of the air-sea CO2 flux in mangrove tidal creeks directly resulting from pore water exchange has seldom been accurately quantified.
The observation in the mangrove-dominated creek shows that the tidal creek is the hot spot of CO2 emission in the mangrove system in both wet and dry seasons, as observed in other mangrove systems (Kristensen et al., 2008; Taillardat et al., 2018; Call et al., 2019), and the air-water CO2 exchange flux of tidal creek in our study area is low in the global mangroves (Table 2). Furthermore, the contribution of pore water exchange to the CO2 emission flux in the tidal creek is more than 50% than that in both seasons, which proves that pore water exchange is the main driving factor of air-water CO2 flux in the mangrove tidal creek (Chen et al., 2021b). This also means that these carbon, which is believed to have been stored in the soil for thousands of years (Page et al., 2002), will be re-discharged to coastal waters via pore water exchange, and then returned to the atmosphere through air-water interface exchange.
In addition, the daily average air-water CO2 flux in the S. alterniflora-dominated creek was 20% lower than in the mangrove-dominated creek (Fig. S1a). With the same water temperature, salinity, wind speed, and air pressure used in the flux calculation at the two stations in the creeks, the difference in the air-water CO2 fluxes between the two stations was mainly caused by the difference in pCO2 in the tidal creeks as the pCO2 in the S. alterniflora-dominated creek was lower by 32% than in the mangrove-dominated creek (Fig. 3). As pore water exchange was a main regulator of pCO2 in the tidal creeks, we infer that the less emission in the S. alterniflora-dominated creek was mainly caused by the relatively weak pore water exchange (Fig. S1b).
To estimate the lateral carbon transport in the creeks, carbon outwelling was estimated by integration over a diel cycle of the product of the carbon concentration and the water flow (Maher et al., 2013). Since the Zhangjiang River had a relatively small discharge and the creeks were dominated by tidal flows, the same water depth was ensured at the beginning and end of the integration period. The results showed that in the mangrove-dominated creek, there was a net export downstream of DIC (1.87 mol/(m2∙d)) and DOC (0.42 mol/(m2∙d)) in the wet season. In the dry season, the tidal creek exported greater DC downstream with 2.34 mol/(m2∙d) for DIC and 0.54 mol/(m2∙d) for DOC. The carbon carried by the pore water exchange in the form of DIC accounted for 100% of the DIC outwelling from the tidal creek. In the DC outwelling about 80% was in form of DIC in both seasons. This is similar to the results in the tidal creek of Evans head, Australia (Santos et al., 2019). In the S. alterniflora-dominated creek, an outwelling of DC of 2.88 mol/(m2∙d) occurred in the dry season, which included 3.17 mol/(m2∙d) for DIC and −0.29 mol/(m2∙d) for DOC, indicating that the DC outwelling was 100% in the form of DIC. Similar to the mangrove-dominated creek, the DC transported by the pore water exchange in the form of DIC accounted for 79% of the DIC outwelling from the tidal creek. Our results indicate that most of the carbon carried by the pore water exchange into the creeks was exported to the ocean in the form of DIC under the pumping of tides. We highlight that since only one day measurements have been carried out in each creek, and there was only one station in each landscape, it was impossible to draw a statistical conclusion. But the difference between the two stations still indicates that the invasion of S. alterniflora may have changed the fate of carbon fixed in the intertidal wetlands.
To evaluate the impact of net carbon export from soils via pore water exchange into the creeks of the mangrove-S. alterniflora ecozone, we compiled the known carbon sources and sinks of the system and set up a conceptual framework of the fate of carbon fixed by the vegetations in the ecozone as follows (Fig. 7). The vegetation absorbs carbon in the form of CO2 from the atmosphere through photosynthesis. Some of the fixed carbon is respired by the vegetation to CO2 and directly released back to the atmosphere, while the other fixed carbon is stored in the vegetation or buried in the soil or exported via pore water exchange. The DIC fluxes via pore water exchange were greater than the DOC fluxes, suggesting that DIC was the main form of carbon exported by pore water exchange (Fig. 6), which confirms the missing mangrove carbon sink being the pore water-exported DIC (Maher et al., 2013). Note that the pore water exchange occurs in the tidal creeks, while the net primary production and carbon accretion in the mangrove system are intended for the whole mangrove-covered region. The soil carbon accretion is a net result of gross carbon burial in the soil and pore water exchange. The total area of tidal creeks in the mangroves of the ecozone is about 2.87×104 m2, while the total mangrove-covered area is 5.74×105 m2 (Fig. 1). The carbon via pore water exchange in the tidal creeks of the mangrove system, calculated as the carbon flux via pore water exchange multiplied by the total area of the tidal creeks, was (6.17×104−8.23×104) mol/d. The net carbon fixed by mangrove vegetation was estimated with the net ecosystem CO2 exchange, 0.26 mol/(m2∙d) (Zhu et al., 2021), multiplied by the total mangrove-covered area, to be 1.49×105 mol/d. The amount of soil carbon accretion was 2.29×104 mol/d, calculated with the mangrove-covered area multiplied by the soil carbon accretion rate of 0.04 mol/(m2∙d) (Chen et al., 2021a). Thus, the carbon via pore water exchange in the tidal creeks of the mangrove system accounted for 41%−55% of the net carbon fixed by mangrove vegetation and 3−4 times as much as the soil carbon accretion. Less than 5% of the carbon exported from the soil via pore water exchange is released in the form of CO2 from the creeks as the pCO2 in the creeks increases due to the DIC addition from pore water exchange. The DIC exported from soils via pore water accounts for 79%−100% of the DIC outwelling into the estuary from the mangrove-S. alterniflora ecozone. The results confirm that a major export pathway for carbon from mangroves is through root and soil respiration and subsequent dissolved inorganic carbon export via pore water (Alongi, 2014, 2020). The residence time of DIC (mostly as alkalinity) in the ocean is about 100 000 a (Santos et al., 2019; Yau et al., 2022), making DIC outwelling from the mangrove-S. alterniflora ecozone a long-term storage mechanism for the carbon fixed by the mangroves and S. alterniflora in addition to burial in the soil. Similarly, in the mangrove creeks in Australia (Maher et al., 2013) and Vietnam (Taillardat et al., 2018), pore water exchange traced by radon can explain nearly 100% of the DIC outwelling. Such a great carbon loss term in the subtropical mangrove-Spartina ecozone of the Zhangjiang River Estuary confirms that the ability of the blue carbon habitat to effectively fix carbon has been highly underestimated as observed in other mangroves (Maher et al., 2018). Globally, only about 13% of the carbon absorbed by mangrove vegetation via photosynthesis has been deposited in the soil (Alongi, 2014). Therefore, quantification of the pore water exchange and related soil carbon loss is essential to fully understand their carbon fixation capacity.
In this study, we quantified the dissolved carbon flux via pore water exchange and assessed the fate of the exported carbon in the mangrove-Spartina ecozone in the Zhangjiang River Estuary, China. The dissolved carbon flux based on the mass balance of 222Rn and 228Ra was (2.15 ± 0.63) mol/(m2∙d) in the wet season and (2.87 ± 0.65) mol/(m2∙d) in the dry season in the mangrove-dominated creek and 11% lower in the S. alterniflora-dominated creek, which was about 6−8 times greater than the riverine input in both seasons in the tidal creeks of the ecozone. The smaller export of dissolved carbon from soils via pore water exchange in the S. alterniflora-dominated creek implies similar occurrence likely in other regions where S. alterniflora invades. The pore water exchange in the ecozone contributed 54%−84% of the emission of CO2 from the tidal creeks. The dissolved carbon exported from soils via pore water exchange to the tidal creeks were found to be in the form of DIC, which accounted for all of the DIC outwelling from the mangrove-dominated creek and 79% of the DIC outwelling from the S. alterniflora creek.
Acknowledgements: We express our sincere gratitude to Captain Zhaorong Wang from Zhangzhou, Fujian Province, China for his assistance in collecting the pore water samples. We also extend our gratitude to the two anonymous reviewers for all their constructive comments which helped improving the quality of manuscript.|
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Supplementary information.pdf
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| 1. | Jian’an Liu, Xueqing Yu, Xinyi Lin, et al. The importance of porewater exchange process on carbon lateral export from saltmarsh creek to coastal sea. Journal of Oceanology and Limnology, 2024. doi:10.1007/s00343-024-3261-3 | |
| 2. | Jing Zhou, Jinzhou Du, Kaijun Su, et al. Substantially excess uranium in the waters of an intertidal salt marsh: A case study of eastern Chongming Beach. Estuarine, Coastal and Shelf Science, 2023. doi:10.1016/j.ecss.2023.108585 |
Figures(7) / Tables(2)
Supported by:
Beijing Renhe Information Technology Co. Ltd
Weizhen Jiang, Guizhi Wang, Qing Li, Manab Kumar Dutta, Shilei Jin, Guiyuan Dai, Yi Xu. The fate of carbon resulting from pore water exchange in a mangrove and Spartina alterniflora ecozone[J]. Acta Oceanologica Sinica, 2023, 42(8): 61-76. doi: 10.1007/s13131-023-2234-2
| Season | ID | Latitude | Longitude | Depth/m | Salinity | 222Rn/ (Bq∙m−3) | 226Ra/ (dpm∙(100 L)−1) | 228Ra/ (dpm∙(100 L)−1) | DIC/ (μmol∙L−1) | TA/ (μmol∙L−1) | DOC (μmol∙L−1) |
| Wet season | PW 1 | 23.9270°N | 117.4174°E | 0.5 | 12.7 | 3070 | 203 | 802 | 5355 | 4061 | 359 |
| PW 2 | 23.9270°N | 117.4174°E | 0.5 | 12.0 | 3070 | 193 | 847 | 6169 | 4336 | 343 | |
| PW 3 | 23.9261°N | 117.4164°E | 0.5 | 11.0 | 2210 | 176 | 750 | 3050 | 2605 | 258 | |
| PW 4 | 23.9259°N | 117.4186°E | 0.5 | 12.4 | 4630 | 154 | 1024 | 4023 | 3382 | 425 | |
| PW 5 | 23.9253°N | 117.4186°E | 0.5 | 11.0 | 1240 | 154 | 934 | 2784 | 2519 | 254 | |
| PW 6 | 23.9222°N | 117.4233°E | 0.5 | 13.2 | 1280 | 192 | 1225 | 4252 | 3916 | 323 | |
| PW 7 | 23.9158°N | 117.4308°E | 0.5 | 9.6 | 2350 | 99 | 501 | 2579 | 2383 | 315 | |
| PW 8 | 23.9317°N | 117.4335°E | 0.5 | 12.7 | 4600 | 118 | 489 | 5271 | 4706 | 288 | |
| PW 10 | 23.9253°N | 117.4294°E | 0.5 | 11.0 | 1620 | 145 | 600 | 2246 | 2129 | 206 | |
| Well 1 | 23.9247°N | 117.4109°E | 0 | 1.1 | 139000 | 81 | 67 | 6306 | 4173 | 46 | |
| Well 2 | 23.9204°N | 117.4138°E | 0 | 0.0 | 36700 | 55 | 38 | 1891 | 1168 | 11 | |
| SED 3 | 23.9261°N | 117.4150°E | 0.1 | − | 1280 | − | − | − | − | − | |
| SED 4 | 23.9261°N | 117.4164°E | 0.1 | − | 550 | − | − | − | − | − | |
| SED 6 | 23.9253°N | 117.4186°E | 0.1 | − | 543 | − | − | − | − | − | |
| SED 7 | 23.9222°N | 117.4233°E | 0.1 | − | 170 | − | − | − | − | − | |
| SED 10 | 23.9253°N | 117.4294°E | 0.1 | − | 543 | − | − | − | − | − | |
| ZJ | 23.9528°N | 117.3613°E | 0 | 0.0 | 880 | 29 | 41 | 518 | 392 | 149 | |
| SW | 23.9147°N | 117.4706°E | 0 | 20.1 | 77 | 63 | 181 | 1528 | 1623 | 154 | |
| Dry season | PW 1 | 23.9270°N | 117.4174°E | 0.5 | 17.3 | 4030 | 145 | 676 | 3061 | 2030 | 187 |
| PW 3 | 23.9270°N | 117.4164°E | 0.5 | 22.0 | 1410 | 189 | 1005 | 3336 | 3104 | 465 | |
| PW 4 | 23.9261°N | 117.4186°E | 0.5 | 20.3 | 3830 | 147 | 677 | 5296 | 4767 | 322 | |
| PW 6 | 23.9259°N | 117.4233°E | 0.5 | 22.4 | 1580 | 224 | 1143 | 3507 | 3027 | 214 | |
| PW 7 | 23.9253°N | 117.4308°E | 0.5 | 22.8 | 2980 | 122 | 651 | 3121 | 2756 | 384 | |
| PW 8 | 23.9222°N | 117.4335°E | 0.5 | 22.3 | 5130 | 166 | 853 | 7577°N | 7128°E | 300 | |
| PW 10 | 23.9158°N | 117.4294°E | 0.5 | 22.6 | 2630 | 58 | 203 | 3033 | 2749 | 262 | |
| Well 1 | 23.9317°N | 117.4109°E | 0 | 0.9 | 111000 | 77 | 78 | 6775 | 3766 | 62 | |
| Well 2 | 23.9253°N | 117.4138°E | 0 | 0.0 | 37700 | 25 | 30 | 2138 | 1139 | 77 | |
| Well 3 | 23.9242°N | 117.4128°E | 0 | 0.0 | 33100 | 22 | 34 | 4205 | 2716 | 54 | |
| Well 4 | 23.9242°N | 117.4136°E | 0 | 0.0 | 112000 | 69 | 46 | 3116 | 1803 | 39 | |
| SED 3 | 23.9247°N | 117.4150°E | 0.1 | − | 737 | − | − | − | − | − | |
| SED 4 | 23.9204°N | 117.4164°E | 0.1 | − | 0 | − | − | − | − | − | |
| SED 5 | 23.9261°N | 117.4186°E | 0.1 | − | 373 | − | − | − | − | − | |
| SED 6 | 23.9261°N | 117.4233°E | 0.1 | − | 377 | − | − | − | − | − | |
| SED 7 | 23.9253°N | 117.4294°E | 0.1 | − | 373 | − | − | − | − | − | |
| SED 9 | 23.9158°N | 117.4308°E | 0.1 | − | 547 | − | − | − | − | − | |
| ZJ | 23.9528°N | 117.3613°E | 0 | 0.0 | 610 | 19 | 29 | 628 | 658 | 160 | |
| SW | 23.9147°N | 117.4706°E | 0 | 26.2 | 127 | 36 | 154 | 1939 | 2046 | 141 | |
| Note: PW represents pore water; Well, well water; SED, the interstitial water of sediments; ZJ, the Zhangjiang River endmember; and SW, the seawater endmember; DIC, dissolved inorganic concentration; DOC, dissolved organic concentration; TA, total alkalinity. 222Rn, 226Ra and 228Ra parameters indicate their activity concentrations. − represents no data. | |||||||||||
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CSV
| Type | Study area | PER/ (cm∙d−1) | Mean SCD/ (mg∙cm−3) | Mean CAR/ (g∙m−2 ∙a−1) | CO2 flux/ (mmol∙m−2∙d−1) | Reference |
| Delta | North Queensland, Australia | 80−990 | 29.1 ± 1.3 | 138 ± 36 | 9.4−114 | Alongi et al. (1999); Brunskill et al. (2002); Call et al. (2015); Sanders et al. (2016); Susilo et al. (2005); Tait et al. (2017) |
| Delta | northwest coast of Indonesia | − | 25.9 ± 3.2 | 426 ± 236 | 32.2−93.1 | Chen et al. (2014); Alongi (2012); Alongi et al. (2008); Donato et al. (2011); Kusumaningtyas et al. (2019); Rovai and Twilley (2021) |
| Delta | Panay Island, Philippines | − | 14.6 ± 2.9 | 214 ± 58 | − | MacKenzie et al. (2021); Thompson et al. (2014) |
| Delta | southwestern coast of the gulf, Thailand | − | 21.2 ± 1.6 | 224 ± 21 | 150 | Alongi et al. (2001); Monji et al. (2002) |
| Delta | ThanHoa, Vietnam | 4.9 | 12.5 ± 1.1 | 150 ± 30 | 34.2−155 | Grellier et al. (2017); Koné et al. (2008); Taillardat et al. (2018); Tateda et al. (2005) |
| Delta | northern Gulf of Mexico, United States | 68 | − | 450 | − | Henry and Twilley (2013); Kelly et al. (2019); Yando et al. (2016) |
| Estuary | Ceará, Brazil | 8−15 | 27.0 ± 3.1 | 651 ± 298 | 60.5−112 | Burnett et al. (2008); Pülmanns et al. (2014); Passos et al. (2016); Rovai et al. (2018); Sanders et al. (2010), Sanders et al. (2012) |
| Estuary | southeastern India | 237−747 | 15.6 ± 0.5 | − | 0.4−70.2 | Bouillon et al. (2003); Biswas et al. (2004); Prakash et al. (2018); Ranjan et al. (2011); Ray et al. (2011) |
| Estuary | Northwest Madagascar | − | 23.4 ± 3.8 | 110 | 43.6 | Arias-Ortiz et al. (2021); Borges (2003); Jones et al. (2014) |
| Estuary | Zhangjiang River Estuary, China | 82.1−110 | 15.8 | 155 | 7.1−11.6 | this study; Chen et al. (2021a) |
| Lagoon | Lagunade Terminos, Mexico | − | 49.8 ± 3.8 | 97 ± 29 | − | Adame et al. (2013); Gonneea et al. (2004); Kauffman et al. (2016); Lynch et al. (1989) |
| Lagoon | Gulf of Mexico, United States | 0.7−24.3 | 29.5 ± 5.6 | 116 ± 33 | 4.6 | Bianchi et al. (2013); Millero et al. (2001); Rovai and Twilley (2021); Rovai et al. (2018); Swarzenski et al. (2009); Yando et al. (2016) |
| Open coast | Arabian Gulf of Saudi Arabia | − | − | 19 ± 4 | − | Cusack et al. (2018) |
| Note: PER: pore water exchange rate; SCD: soil carbon density; CAR: carbon accretion rate. − represents no data. | ||||||
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CSV
| Season | ID | Latitude | Longitude | Depth/m | Salinity | 222Rn/ (Bq∙m−3) | 226Ra/ (dpm∙(100 L)−1) | 228Ra/ (dpm∙(100 L)−1) | DIC/ (μmol∙L−1) | TA/ (μmol∙L−1) | DOC (μmol∙L−1) |
| Wet season | PW 1 | 23.9270°N | 117.4174°E | 0.5 | 12.7 | 3070 | 203 | 802 | 5355 | 4061 | 359 |
| PW 2 | 23.9270°N | 117.4174°E | 0.5 | 12.0 | 3070 | 193 | 847 | 6169 | 4336 | 343 | |
| PW 3 | 23.9261°N | 117.4164°E | 0.5 | 11.0 | 2210 | 176 | 750 | 3050 | 2605 | 258 | |
| PW 4 | 23.9259°N | 117.4186°E | 0.5 | 12.4 | 4630 | 154 | 1024 | 4023 | 3382 | 425 | |
| PW 5 | 23.9253°N | 117.4186°E | 0.5 | 11.0 | 1240 | 154 | 934 | 2784 | 2519 | 254 | |
| PW 6 | 23.9222°N | 117.4233°E | 0.5 | 13.2 | 1280 | 192 | 1225 | 4252 | 3916 | 323 | |
| PW 7 | 23.9158°N | 117.4308°E | 0.5 | 9.6 | 2350 | 99 | 501 | 2579 | 2383 | 315 | |
| PW 8 | 23.9317°N | 117.4335°E | 0.5 | 12.7 | 4600 | 118 | 489 | 5271 | 4706 | 288 | |
| PW 10 | 23.9253°N | 117.4294°E | 0.5 | 11.0 | 1620 | 145 | 600 | 2246 | 2129 | 206 | |
| Well 1 | 23.9247°N | 117.4109°E | 0 | 1.1 | 139000 | 81 | 67 | 6306 | 4173 | 46 | |
| Well 2 | 23.9204°N | 117.4138°E | 0 | 0.0 | 36700 | 55 | 38 | 1891 | 1168 | 11 | |
| SED 3 | 23.9261°N | 117.4150°E | 0.1 | − | 1280 | − | − | − | − | − | |
| SED 4 | 23.9261°N | 117.4164°E | 0.1 | − | 550 | − | − | − | − | − | |
| SED 6 | 23.9253°N | 117.4186°E | 0.1 | − | 543 | − | − | − | − | − | |
| SED 7 | 23.9222°N | 117.4233°E | 0.1 | − | 170 | − | − | − | − | − | |
| SED 10 | 23.9253°N | 117.4294°E | 0.1 | − | 543 | − | − | − | − | − | |
| ZJ | 23.9528°N | 117.3613°E | 0 | 0.0 | 880 | 29 | 41 | 518 | 392 | 149 | |
| SW | 23.9147°N | 117.4706°E | 0 | 20.1 | 77 | 63 | 181 | 1528 | 1623 | 154 | |
| Dry season | PW 1 | 23.9270°N | 117.4174°E | 0.5 | 17.3 | 4030 | 145 | 676 | 3061 | 2030 | 187 |
| PW 3 | 23.9270°N | 117.4164°E | 0.5 | 22.0 | 1410 | 189 | 1005 | 3336 | 3104 | 465 | |
| PW 4 | 23.9261°N | 117.4186°E | 0.5 | 20.3 | 3830 | 147 | 677 | 5296 | 4767 | 322 | |
| PW 6 | 23.9259°N | 117.4233°E | 0.5 | 22.4 | 1580 | 224 | 1143 | 3507 | 3027 | 214 | |
| PW 7 | 23.9253°N | 117.4308°E | 0.5 | 22.8 | 2980 | 122 | 651 | 3121 | 2756 | 384 | |
| PW 8 | 23.9222°N | 117.4335°E | 0.5 | 22.3 | 5130 | 166 | 853 | 7577°N | 7128°E | 300 | |
| PW 10 | 23.9158°N | 117.4294°E | 0.5 | 22.6 | 2630 | 58 | 203 | 3033 | 2749 | 262 | |
| Well 1 | 23.9317°N | 117.4109°E | 0 | 0.9 | 111000 | 77 | 78 | 6775 | 3766 | 62 | |
| Well 2 | 23.9253°N | 117.4138°E | 0 | 0.0 | 37700 | 25 | 30 | 2138 | 1139 | 77 | |
| Well 3 | 23.9242°N | 117.4128°E | 0 | 0.0 | 33100 | 22 | 34 | 4205 | 2716 | 54 | |
| Well 4 | 23.9242°N | 117.4136°E | 0 | 0.0 | 112000 | 69 | 46 | 3116 | 1803 | 39 | |
| SED 3 | 23.9247°N | 117.4150°E | 0.1 | − | 737 | − | − | − | − | − | |
| SED 4 | 23.9204°N | 117.4164°E | 0.1 | − | 0 | − | − | − | − | − | |
| SED 5 | 23.9261°N | 117.4186°E | 0.1 | − | 373 | − | − | − | − | − | |
| SED 6 | 23.9261°N | 117.4233°E | 0.1 | − | 377 | − | − | − | − | − | |
| SED 7 | 23.9253°N | 117.4294°E | 0.1 | − | 373 | − | − | − | − | − | |
| SED 9 | 23.9158°N | 117.4308°E | 0.1 | − | 547 | − | − | − | − | − | |
| ZJ | 23.9528°N | 117.3613°E | 0 | 0.0 | 610 | 19 | 29 | 628 | 658 | 160 | |
| SW | 23.9147°N | 117.4706°E | 0 | 26.2 | 127 | 36 | 154 | 1939 | 2046 | 141 | |
| Note: PW represents pore water; Well, well water; SED, the interstitial water of sediments; ZJ, the Zhangjiang River endmember; and SW, the seawater endmember; DIC, dissolved inorganic concentration; DOC, dissolved organic concentration; TA, total alkalinity. 222Rn, 226Ra and 228Ra parameters indicate their activity concentrations. − represents no data. | |||||||||||
| Type | Study area | PER/ (cm∙d−1) | Mean SCD/ (mg∙cm−3) | Mean CAR/ (g∙m−2 ∙a−1) | CO2 flux/ (mmol∙m−2∙d−1) | Reference |
| Delta | North Queensland, Australia | 80−990 | 29.1 ± 1.3 | 138 ± 36 | 9.4−114 | Alongi et al. (1999); Brunskill et al. (2002); Call et al. (2015); Sanders et al. (2016); Susilo et al. (2005); Tait et al. (2017) |
| Delta | northwest coast of Indonesia | − | 25.9 ± 3.2 | 426 ± 236 | 32.2−93.1 | Chen et al. (2014); Alongi (2012); Alongi et al. (2008); Donato et al. (2011); Kusumaningtyas et al. (2019); Rovai and Twilley (2021) |
| Delta | Panay Island, Philippines | − | 14.6 ± 2.9 | 214 ± 58 | − | MacKenzie et al. (2021); Thompson et al. (2014) |
| Delta | southwestern coast of the gulf, Thailand | − | 21.2 ± 1.6 | 224 ± 21 | 150 | Alongi et al. (2001); Monji et al. (2002) |
| Delta | ThanHoa, Vietnam | 4.9 | 12.5 ± 1.1 | 150 ± 30 | 34.2−155 | Grellier et al. (2017); Koné et al. (2008); Taillardat et al. (2018); Tateda et al. (2005) |
| Delta | northern Gulf of Mexico, United States | 68 | − | 450 | − | Henry and Twilley (2013); Kelly et al. (2019); Yando et al. (2016) |
| Estuary | Ceará, Brazil | 8−15 | 27.0 ± 3.1 | 651 ± 298 | 60.5−112 | Burnett et al. (2008); Pülmanns et al. (2014); Passos et al. (2016); Rovai et al. (2018); Sanders et al. (2010), Sanders et al. (2012) |
| Estuary | southeastern India | 237−747 | 15.6 ± 0.5 | − | 0.4−70.2 | Bouillon et al. (2003); Biswas et al. (2004); Prakash et al. (2018); Ranjan et al. (2011); Ray et al. (2011) |
| Estuary | Northwest Madagascar | − | 23.4 ± 3.8 | 110 | 43.6 | Arias-Ortiz et al. (2021); Borges (2003); Jones et al. (2014) |
| Estuary | Zhangjiang River Estuary, China | 82.1−110 | 15.8 | 155 | 7.1−11.6 | this study; Chen et al. (2021a) |
| Lagoon | Lagunade Terminos, Mexico | − | 49.8 ± 3.8 | 97 ± 29 | − | Adame et al. (2013); Gonneea et al. (2004); Kauffman et al. (2016); Lynch et al. (1989) |
| Lagoon | Gulf of Mexico, United States | 0.7−24.3 | 29.5 ± 5.6 | 116 ± 33 | 4.6 | Bianchi et al. (2013); Millero et al. (2001); Rovai and Twilley (2021); Rovai et al. (2018); Swarzenski et al. (2009); Yando et al. (2016) |
| Open coast | Arabian Gulf of Saudi Arabia | − | − | 19 ± 4 | − | Cusack et al. (2018) |
| Note: PER: pore water exchange rate; SCD: soil carbon density; CAR: carbon accretion rate. − represents no data. | ||||||
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