Partitioning of carbon export in the upper water column of the oligotrophic South China Sea

Ma, Yifan; Zhou, Kuanbo; Chen, Weifang; Chen, Junhui; Yang, Jin-Yu Terence; Dai, Minhan

doi:https://doi.org/10.5194/bg-2022-196

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https://doi.org/10.5194/bg-2022-196

Preprints

07 Oct 2022

| 07 Oct 2022

Status: a revised version of this preprint is currently under review for the journal BG.

Partitioning of carbon export in the upper water column of the oligotrophic South China Sea

Yifan Ma, Kuanbo Zhou, Weifang Chen, Junhui Chen, Jin-Yu Terence Yang, and Minhan Dai

Abstract. We conducted high vertical resolution samplings of total and particulate ²³⁴Th along with particulate organic carbon (POC) in the summer of 2017 to examine nutrient-dependent structures of export productivity within the euphotic zone (Ez) of the oligotrophic basin of the South China Sea (SCS). Nitrate concentrations throughout the study area were below detection limit in the nutrient-depleted layer (NDL) above the nutricline, while they sharply increased with depth in the nutrient-replete layer (NRL) across the nutricline until the base of the Ez. Based on our high resolution vertical profilings of ²³⁴Th/²³⁸U disequilibria, this study for the first time estimated POC export fluxes both out of the NDL and at the horizon of the Ez base. Total ²³⁴Th deficit relative to ²³⁸U occurred in the NDL at all study sites, while ²³⁴Th was mostly in equilibrium with ²³⁸U in the NRL except at the northmost station SEATS (116° E, 18° N), where the ²³⁴Th deficit could also be observed in the NRL. By combining 1D steady-state ²³⁴Th fluxes and POC/²³⁴Th ratios, we derived vertical patterns of POC export fluxes. Values were 1.6±0.6 mmol C m^-2 d^-1 at the NDL base, representing approximately half of the flux estimated at the base of the Ez at station SEATS; for the rest of the sampling sites, POC export fluxes at the NDL base (averaged at 2.3±1.1 mmol C m^-2 d^-1) were identical within error to those at the base of the Ez (1.9±0.5 mmol C m^-2 d^-1), suggesting rapid export of POC out of the NDL. This finding fundamentally changes our traditional view that the NDL, being depleted in nutrients, would not be a net exporter of POC. Based on the positive relationship between POC export fluxes at the NDL base and supply potential of subsurface nutrients (i.e., nutricline depth and nutrient concentrations), we found that POC export fluxes (averaged at 3.4±1.2 mmol C m^-2 d^-1) at the NDL base at stations with shallow nutriclines and high subsurface nutrient concentrations were ~100 % higher than the fluxes (averaged at 1.6±0.5 mmol C m^-2 d^-1) at other stations. We used a two-endmember mixing model based on the mass and ¹⁵N-isotopic balances to further evaluate the potential sources of new nitrogen that could support the observed particle export at stations SEATS and SS1, located respectively in the northern and southern basin of the SCS with different hydrological features. We showed that more than 50 % of the particle flux out of the NDL was supported by nitrate sources other than atmospheric deposition and nitrogen fixation: likely supply from depth associated with episodic intrusions. However, the exact mechanisms and pathways for subsurface nutrients to support the export production from the NDL merit careful and dedicated studies.

Received: 22 Sep 2022 – Discussion started: 07 Oct 2022

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Yifan Ma et al.

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RC1: 'Comment on bg-2022-196', Anonymous Referee #1, 20 Oct 2022

Ma et al. calculated POC export fluxes at the base of the NDL and Ez, as well as discussed the NDL's nutrient source. The data is treasurable for understanding nutrient dynamics and the carbon cycle. The outcome is reliable, and the manuscript is well-organized. However, some points must be clarified before accepting for publication. There are also a number of typos. My specific recommendations are listed below.

My biggest concern is about the method calculating the physical transport flux. In eq. 8, V is part of the tendency term shown in eq. 3. To calculate the horizontal transport flux in the NDL or Ez, it needs to implement an integration over the depth. Whereas, the vertical flux is calculated as the wC, where w is the vertical velocity and C is the concentration of the tracer. It isn’t necessary to calculate the “integrated vertical transport flux” over the NDL or Ez as shown in L306. Please recheck your method. I listed some references that introduce the method to calculate transport fluxes. The authors need to introduce how they calculated the horizontal and vertical fluxes clearly.

Palter, J.B., Marinov, I., Sarmiento, J.L., Gruber, N. (2013). Large-Scale, Persistent Nutrient Fronts of the World Ocean: Impacts on Biogeochemistry. In: The Handbook of Environmental Chemistry. Springer, Berlin, Heidelberg. https://doi.org/10.1007/698_2013_241

McGillicuddy, D. J., Anderson, L. A., Doney, S. C., and Maltrud, M. E. (2003), Eddy-driven sources and sinks of nutrients in the upper ocean: Results from a 0.1° resolution model of the North Atlantic, , 17, 1035, doi:10.1029/2002GB001987

In section 4.3.2, the authors calculated the mass balance of 15N (Eqs. 10, 11). In my understanding, PN which denote particulate nitrogen should be interpreted when it occurred for the first time. It is not clear how to calculate the 3 unknows (Fpn, Fno3, Fair) in two equations. Please introduce the calculation carefully.
The authors discovered that horizontal transport flux accounts for 20% of total flux. However, the fraction is not negligible. Some stations were shown to be influenced by eddy activities. It is worthwhile to consider the horizontal transport of eddies whose effect is not only vertical. There are some studies discussed the horizontal transport of particles in eddies e.g. Wang et al., 2018 http://dx.doi.org/10.1029/2017JC013623, Ma et al., 2021, http://dx.doi.org/10.1016/j.pocean.2021.102566. Can you separate the nutrients trapped in the cyclonic eddy and transported with the eddy (horizontal transport) and local uplifted nutrients (vertical transport)? Stations B1 and C2 may be affected by the upwelling off the coast of Vietnam.

Minor concerns:

L36: Siegel et al., 2021
L41-42: Need references
L53: the references are not recent ones. Don’t use the word recently.
Figure 1: Denote the shading and add a color bar
Please consider to make a new table to show the location, water depth, sampling depth, sampling time etc.
Eq. 3 is the same as Eq. 1.
The font is too small in Figure 4.
Eq9. What’s the delta x and delta y.

Citation: https://doi.org/10.5194/bg-2022-196-RC1

AC1: 'Reply on RC1', Minhan Dai, 20 Jan 2023

Publisher’s note: the supplement to this comment was removed on 20 January 2023.

Interactive comment on “Partitioning of carbon export in the upper water column of the oligotrophic South China Sea” by Yifan Ma et al

Yifan Ma¹, Kuanbo Zhou¹. Weifang Chen¹, Junhui Chen¹, Jin-Yu Terence Yang¹ & Minhan Dai¹

¹State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China

Correspondence to: Minhan Dai (mdai@xmu.edu.cn)

Anonymous Referee #1

[Response]: We appreciate the positive comments from the reviewer. Our point-by-point responses are listed as of below.

Specific recommendations

My biggest concern is about the method calculating the physical transport flux. In eq. 8, V is part of the tendency term shown in eq. 3. To calculate the horizontal transport flux in the NDL or Ez, it needs to implement an integration over the depth. Whereas, the vertical flux is calculated as the wC, where w is the vertical velocity and C is the concentration of the tracer. It isn’t necessary to calculate the “integrated vertical transport flux” over the NDL or Ez as shown in L306. Please recheck your method. I listed some references that introduce the method to calculate transport fluxes. The authors need to introduce how they calculated the horizontal and vertical fluxes clearly.

[Response]: The reviewer is correct that integration for calculation of vertical transport flux of ²³⁴Th is unnecessary. We have double checked the calculation of vertical transport flux of ²³⁴Th at the base of the NDL and the Ez. The w and K_z at the base of Ez (110 m) were -0.10 m d^-1 and 0.86 m² d^-1, respectively from Gan et al. (2016). The ²³⁴Th activity at 125 m and 100 m was 2.44±0.04 and 2.50±0.02 dpm L^-1, respectively at station SS1. The physical term V of vertical ²³⁴Th flux was estimated to be -2.0±0.4 dpm m^-2 d^-1 at the base of Ez based on the following equation (adapted from McGillicuddy et al., (2003) as recommended by the reviewer): where, is the distance between sampling depths. The estimated vertical flux of ²³⁴Th at the NDL base was -11.4±0.1 dpm m^-2 d^-1 at station SS1. Therefore, the physical term could still be neglected. We will revise the text as: “The vertical transport fluxes were estimated to be -2.0±0.4 and -11.4±0.1 dpm m^-2 d^-1 at the base of Ez and NDL, respectively, accounting for <10% of the vertical scavenging fluxes at corresponding layers at the station SS1, which can be considered to be negligible.”

In section 4.3.2, the authors calculated the mass balance of ¹⁵N (Eqs. 10, 11). In my understanding, PN which denote particulate nitrogen should be interpreted when it occurred for the first time. It is not clear how to calculate the 3 unknows (Fpn, Fno3,

Fair) in two equations. Please introduce the calculation carefully.

[Response]: Following suggestions, we will explain “PN” at its first appearance, which will read: “POC and particulate nitrogen (PN) concentrations were determined by an Elemental Analyzer-Isotope Ratio Mass Spectrometer (EA-IRMS) system…”.

In addition, we have rephrased the parameters and changed Equations 10 &11 as follows: “

=+ (10)

(11)

where, and represent the fraction of PN export contributed by upwelled DIN from the subsurface and by atmospheric deposition and N₂ fixation, respectively. and δ¹⁵N_air denote the endmembers of δ¹⁵N for DIN in subsurface waters and air-derived N, respectively.”

The authors discovered that horizontal transport flux accounts for 20% of total flux. However, the fraction is not negligible. Some stations were shown to be influenced by eddy activities. It is worthwhile to consider the horizontal transport of eddies whose effect is not only vertical. There are some studies discussed the horizontal transport of particles in eddies e.g. Wang et al., 2018 http://dx.doi.org/10.1029/2017JC013623, Ma et al., 2021, http://dx.doi.org/10.1016/j.pocean.2021.102566. Can you separate the nutrients trapped in the cyclonic eddy and transported with the eddy (horizontal transport) and local uplifted nutrients (vertical transport)? Stations B1 and C2 may be affected by the upwelling off the coast of Vietnam.

[Response]: We appreciate these important comments from the reviewer aiming for improving the flux estimate. Meanwhile, we have to recognize that the horizontal transport flux of 20% was an upper limit of estimates, which is overall comparable with the magnitude of the uncertainty from²³⁴Th measurements (could be >10%). Therefore, the horizontal flux of <20% of the total flux have been typically omitted in many prior studies given the difficulty in the estimation therein (e.g., Buesseler et al., 2020; Wei et al., 2011). We will add such reasoning in our revision.

We agree with the reviewer that mesoscale eddies impact flux estimations. Unfortunately, such effects of eddies cannot be resolved from the present study. We will add in our revision such potential impacts of mesoscale eddies. The reviewer also made significant comments on different pathways of nutrient trapping. But again, distinguishing these processes is extremely challenging (Guo et al., 2017; Zhao et al., 2021). Nevertheless, we considered the comments from the reviewer and will add the following text: “It is also worthwhile to consider that influences from mesoscale and sub-mesoscale processes in eddies in the SCS basin. Prior studies showed that the concurrence of the vertical transport of particles supported by local uplifted nutrients and the horizontal transport of particles supported by the nutrients trapped in eddies (Wang et al., 2018, Ma et al., 2021). In this study, we found enhanced POC export fluxes at stations with high nutrient inventories, which might infer that the POC export flux might also be supported by nutrients from the subsurface based on the signal of δ¹⁵N_PN. However, our current study was unable to diagnose the pathways of nutrients fuelling the primary and export production.”.

Minor concerns:

L36: Siegel et al., 2021

[Response]: Corrected

L41-42: Need references

[Response]: Accepted. We will add the relevant references in the revision. “(Benitez-Nelson et al., 2001; Cai et al., 2015; Zhou et al., 2020).”

L53: the references are not recent ones. Don’t use the word recently.

[Response]: Accepted and revision will be made accordingly.

Figure 1: Denote the shading and add a color bar.

[Response]: Accepted. We redraw the map and add a color bar in the revised version.

Please consider to make a new table to show the location, water depth, sampling depth, sampling time etc.

[Response]: As suggested by the reviewer, three tables: the location of sampling stations with arriving and leaving time, water bottom depth, parameters and data utilization in the Table R1 and sampling depth with the ²³⁴Th and POC data in Table R2 are available in the revised manuscript.

Table R1: Sampling logs and site information along with the accessed parameters and their utilizations.

Station	Arriving time	Latitude [^oN]	Longitude [^oE]	Bottom depth [m]	Parameters	Data utilizations
Total ²³⁴Th	Trap	Partitioning POC flux estimate	Nutrient source diagnosis
SEATS	2017-06-07 00:06	18	116	3907	√	√	√	√
A1^*	2017-06-11 23:55	16	116	4205	√		√
SS1	2017-06-12 20:08	14	116	4107	√		√
H06	2017-06-20 02:28	14.1	116	4289	√		√
H08	2017-06-20 07:51	13.9	116	4063	√		√
H01	2017-06-20 23:41	14	116.1	4139	√		√
H11	2017-06-21 05:18	14	115.9	4297	√		√
B1	2017-06-22 11:43	14	113	2537	√		√
C1	2017-06-23 04:40	12	113	4313	√		√
A2	2017-06-24 03:05	12	116	4079	√		√
B2	2017-06-24 21:42	14	117	3947	√		√

^*Sampling station might be influenced by the typhoon event passing through the South China Sea. Station A1 was visited after typhoon Merbok, which was generated on June 9, 2017 at 13.1^oN, 119.8^oE in the southern China Sea. Merbok landed on June 12 at 27.5^oN, 117.3^oE.

Table R2: The list of total and particulate ²³⁴Th activity and POC concentration at sampling depth at stations

SEATS	18	116	130	2.55	0.06	0.6	0.13	0.01
SEATS	18	116	100	2.47	0.06	0.8	0.20	0.01
SEATS	18	116	95	2.73	0.07	2.0	0.32	0.01
SEATS	18	116	85	2.41	0.05	2.1	0.39	0.01
SEATS	18	116	75	2.29	0.06	2.4	0.47	0.01
SEATS	18	116	65	2.30	0.06	2.2	0.43	0.01
SEATS	18	116	55	2.03	0.05	1.8	0.41	0.01
SEATS	18	116	45	2.22	0.06	1.3	0.30	0.01
SEATS	18	116	35	2.13	0.05	1.4	0.16	0.01
SEATS	18	116	25	2.30	0.05	1.6	0.12	0.01
SEATS	18	116	15	2.03	0.05	1.2	0.15	0.01
SEATS	18	116	5	2.27	0.05	1.1	0.11	0.01
A1	16	116	100	2.59	0.05	1.1	0.26	0.01
A1	16	116	75	2.47	0.05	2.5	0.26	0.01
A1	16	116	50	2.17	0.05	1.8	0.29	0.01
A1	16	116	25	1.70	0.25	1.3	0.15	0.01
A1	16	116	5	2.34	0.06	1.3	0.11	0.01
SS1	14	116	125	2.44	0.05	0.8	0.25	0.01
SS1	14	116	110	2.42	0.10	0.9	0.27	0.01
SS1	14	116	100	2.39	0.06	1.3	0.42	0.01
SS1	14	116	95	2.50	0.06	1.3	0.41	0.01
SS1	14	116	85	2.32	0.06	1.7	0.41	0.01
SS1	14	116	75	1.98	0.06	1.3	0.30	0.01
SS1	14	116	65	2.06	0.05	1.5	0.35	0.01
SS1	14	116	55	2.35	0.05	1.4	0.23	0.01
SS1	14	116	45	2.15	0.06	0.6	0.20	0.01
SS1	14	116	35	2.04	0.05	1.3	0.14	0.01
SS1	14	116	25	2.15	0.05	1.1	0.18	0.01
SS1	14	116	15	1.99	0.05	1.2	0.17	0.01
SS1	14	116	5	2.15	0.07	1.2	0.19	0.01
H06	14.1	116	100	2.41	0.05	1.4	0.50	0.01
H06	14.1	116	75	2.05	0.05	1.5	0.42	0.01
H06	14.1	116	50	2.33	0.05	1.1	0.19	0.01
H06	14.1	116	25	2.21	0.05	1.0	0.13	0.01
H06	14.1	116	5	2.27	0.05	1.0	0.11	0.01
H08	13.9	116	100	2.39	0.05	1.4	0.30	0.01
H08	13.9	116	75	2.15	0.05	1.9	0.30	0.01
H08	13.9	116	50	2.25	0.05	1.4	0.23	0.01
H08	13.9	116	25	2.21	0.05	1.1	0.25	0.01
H08	13.9	116	5	2.27	0.05	0.9	0.16	0.01
H01	14	116.1	100	2.45	0.05	1.8	0.53	0.01
H01	14	116.1	75	2.25	0.05	1.3	0.22	0.01
H01	14	116.1	50	2.29	0.05	1.8	0.34	0.01
H01	14	116.1	25	2.25	0.05	1.6	0.24	0.01
H01	14	116.1	5	2.10	0.05	1.3	0.15	0.01
H11	14	116.1	100	2.46	0.05	1.3	0.30	0.01
H11	14	116.1	75	2.23	0.04	1.1	0.40	0.01
H11	14	116.1	50	2.25	0.05	1.3	0.13	0.01
H11	14	116.1	25	2.29	0.05	1.0	0.08	0.01
H11	14	116.1	5	2.09	0.04	1.0	0.11	0.01
B1	14	113	100	2.44	0.05	1.4	0.23	0.01
B1	14	113	88	2.08	0.04	2.0	0.52	0.01
B1	14	113	75	2.30	0.08	1.8	0.41	0.01
B1	14	113	50	2.21	0.05	1.4	0.40	0.01
B1	14	113	25	2.24	0.04	1.2	0.08	0.01
B1	14	113	5	2.24	0.05	0.9	0.06	0.01
C1	12	113	100	2.55	0.05	0.7	0.21	0.01
C1	12	113	88	2.49	0.05	0.8	0.25	0.01
C1	12	113	75	2.38	0.04	1.9	0.30	0.01
C1	12	113	50	2.05	0.04	1.5	0.23	0.01
C1	12	113	25	2.10	0.09	1.6	0.25	0.01
C1	12	113	5	2.06	0.04	2.1	0.29	0.01
A2	12	116	100	2.63	0.05	1.1	0.21	0.01
A2	12	116	88	2.21	0.04	0.9	0.42	0.01
A2	12	116	75	2.16	0.04	1.5	0.25	0.01
A2	12	116	50	2.01	0.04	1.5	0.23	0.01
A2	12	116	25	2.18	0.04	1.2	0.09	0.01
A2	12	116	5	1.85	0.06	1.2	0.14	0.01
B2	14	117	108	2.51	0.04	1.1	0.13	0.01
B2	14	117	100	2.49	0.04	0.9	0.27	0.01
B2	14	117	75	2.24	0.04	1.3	0.15	0.01
B2	14	117	50	2.22	0.05	1.8	0.27	0.01
B2	14	117	25	2.40	0.05	1.1	0.12	0.01
B2	14	117	5	2.25	0.05	1.3	0.28	0.01

Eq. 3 is the same as Eq. 1.

[Response]: Fixed. We will revise the equation as:

(3)

The font is too small in Figure 4.

[Response]: We appreciate the reviewer’s comment. We have enlarged the font sizes as of below.

Eq9. What’s the delta x and delta y.

[Response]: We appreciate the reviewer’s comment. Eq. 9 aimed to resolve the horizontally diffusive flux of ²³⁴Th. The and are the distance between the normal stations to evaluate the influences of physical terms ( was the distance between station H06 and H08 and equal to 18 km) in this study.

We will explain the and in our revision: “The and are the distance between the normal stations to evaluate the influences of physical terms (i.e., is the distances between stations H01 and H11; is the distances between stations H06 and H08). and were equal to 18 km in this study.”

References

Benitez-Nelson, C., K. O. Buesseler, D. M. Karl, and J. Andrews: A time-series study of particulate matter export in the North Pacific Subtropical Gyre based on ²³⁴Th: ²³⁸U disequilibrium, Deep-Sea Res I, 48, 2595-2611, 10.1016/S0967-0637(01)00032-2, 2001.

Buesseler, K. O., C. R. Benitez-Nelson, M. Roca-Martí, A. M. Wyatt, L. Resplandy, S. J. Clevenger, J. A. Drysdale, M. L. Estapa, S. Pike, and B. P. Umhau: High-resolution spatial and temporal measurements of particulate organic carbon flux using thorium-234 in the northeast Pacific Ocean during the EXport Processes in the Ocean from RemoTe Sensing field campaign, Elementa-Sci Anthrop, 8, 1, 10.1525/elementa.2020.030, 2020.

Cai, P. H., D. C. Zhao, L. Wang, B. Q. Huang, and M. H. Dai: Role of particle stock and phytoplankton community structure in regulating particulate organic carbon export in a large marginal sea, J Geophys Res-Oceans, 120, 2063-2095, 10.1002/2014jc010432, 2015.

Gan, J. P., Z. Q. Liu, and L. L. Liang: Numerical modeling of intrinsically and extrinsically forced seasonal circulation in the China Seas: A kinematic study, J Geophys Res-Oceans, 121, 4697-4715, 10.1002/2016jc011800, 2016.

Guo, M. X., P. Xiu, S. Y. Li, F. Chai, H. J. Xue, K. B. Zhou, and M. H. Dai: Seasonal variability and mechanisms regulating chlorophyll distribution in mesoscale eddies in the South China Sea, J Geophys Res-Oceans, 122, 5329-5347, 10.1002/2016jc012670, 2017.

Ma, W. T., P. Xiu, F. Chai, L. H. Ran, M. G. Wiesner, J. Y. Xi, Y. W. Yan, and E. Fredj: Impact of mesoscale eddies on the source funnel of sediment trap measurements in the South China Sea, Prog Oceanogr, 194, 10.1016/j.pocean.2021.102566, 2021.

McGillicuddy, D. J., L. A. Anderson, S. C. Doney, and M. E. Maltrud: Eddy-driven sources and sinks of nutrients in the upper ocean: Results from a 0.1 degrees resolution model of the North Atlantic, Global Biogeochem Cy, 17, 10.1029/2002gb001987, 2003.

Wang, L., B. Q. Huang, E. A. Laws, K. B. Zhou, X. Liu, Y. Y. Xie, and M. H. Dai: Anticyclonic Eddy Edge Effects on Phytoplankton Communities and Particle Export in the Northern South China Sea, J Geophys Res-Oceans, 123, 7632-7650, 10.1029/2017jc013623, 2018.

Wei, C. L., S. Y. Lin, D. D. Sheu, W. C. Chou, M. C. Yi, P. H. Santschi, and L. S. Wen: Particle-reactive radionuclides (²³⁴Th, ²¹⁰Pb, ²¹⁰Po) as tracers for the estimation of export production in the South China Sea, Biogeosciences, 8, 3793-3808, 10.5194/bg-8-3793-2011, 2011.

Zhao, D. D., Y. S. Xu, X. G. Zhang, and C. Huang: Global chlorophyll distribution induced by mesoscale eddies, Remote Sens Environ, 254, 10.1016/j.rse.2020.112245, 2021.

Zhou, K. B., M. H. Dai, K. Maiti, W. F. Chen, J. H. Chen, Q. Q. Hong, Y. F. Ma, P. Xiu, L. Wang, and Y. Y. Xie: Impact of physical and biogeochemical forcing on particle export in the South China Sea, Prog Oceanogr, 187, 102403, 10.1016/j.pocean.2020.102403, 2020.

Citation: https://doi.org/10.5194/bg-2022-196-AC1

AC3: 'Reply on RC1', Minhan Dai, 20 Jan 2023

The comment was uploaded in the form of a supplement: https://bg.copernicus.org/preprints/bg-2022-196/bg-2022-196-AC3-supplement.pdf

Citation: https://doi.org/10.5194/bg-2022-196-AC3

RC2: 'Comment on bg-2022-196', Anonymous Referee #2, 15 Dec 2022

The article is rather difficult to follow as the description of the dataset is not clear, and the sections are not always in the appropriate order. For exemple, it is really stange to discuss the impacts oh physical transport on 234^Th fluxes, whereas there were several pages where the 234^Th fluxes and derived product were extensively discussed.

I briefly list different comments the authors need to consider to produce a new version.

The dataset: there is a need of a table that presents clearly sampling, which station / when / what was measured (water column, trap). It is indicated that the cruise took place from June, 5 to 27, 2017. But typhoon Merbok occurred the 10^th. “before our field campaign”. This needs to be clarified. In case of a typhoon had occurred during sampling, one could expect it had impacted the water column and chemical budget. In addition how could it be possible to use the described 234^Th model which is a steady-state model.
Four station (H01, H06, H08, H11) were sampled around SS1 to check the spatial variability of 234^Th. But it is indicated later that the mega station SS1 was revisited during August 2019 (after a second typhon Mun, July, 1th) with trap deployment. A clarification must then to be made on what was sampled / when / where.
High resolutions profiles: the authors made a great announcement about high resolution profiles. In fact there are only two, t detailed profiles : SEAT and SS1. The other profiles have a less resolution, and, except for the lower total 234^Th values at about 25 meters at station A1, the profiles of total 234^Th are not so different. It would be interesting that the authors reduce the depth resolution of the SEAT and SS1 profiles to compare the estimated 234^Th
Export model: from equation (2), the authors need to produce the two equations relative to the export estimate for the NDL- and NRL-layers, respectively. Use directly the symbol for Fndl and Fnrl. There is no need to use layer i /i-1, that only complicate the model presentation. Also from Fig 2, it seems that calculations are done for each boxes, but from the text it is less clear that the fluxes from NRL-layer is calculated considering only the lower box or the whole water column above the euphotic layer limit. Figure 2 needs also to be improved : if total 23Th activities are related to U activities, what means ‘absorb particles , total TH already includes particulate phase. The figure needs to be corrected.
The conversion of 234^TH particulate fluxes in POC fluxes: the conversion is done using the POC/234^TH The recommendation is to use the large particle ratio. In this work, the authors use the ratio obtained from bottle waters, that correspond to fine particles. The authors need to better argument the choice. The comparison with the trap ratio seems to be biased as trap was done in summer, no during the same sampling cruise. The authors need to be clearer on this aspect. If confirmed, it means that some paragraphs are not justified.
Th/POC fluxes estimates: most of the article is based on fluxes, but the authors treated data as it was rather instantaneous fluxes, which is clearly not the case. Considering the half-life of 234^Th, a deficit of 234^Th in the water column represent a flux story of several weeks. The only way to have more “instantaneous” fluxes is to repeat profiles at the same station which was not done here.
Therefore, it is the main problem with the article. The authors discussed a lot fluxes and potential nutrient sources, but the errors on the fluxes estimate do not support the discussion. There is an over-interpretation of the dataset and the derived fluxes to support the hypothesis of the authors.x
Others comments: most figures need to be improved and some data combined differently. What is the interest of figure 3 ?
I do not recommend to accept the present version of the article but I encourage the authors to produce an improved version that presents more clearly the dataset.

Citation: https://doi.org/10.5194/bg-2022-196-RC2

AC2: 'Reply on RC2', Minhan Dai, 20 Jan 2023

Publisher’s note: the supplement to this comment was removed on 20 January 2023.

Interactive comment on “Partitioning of carbon export in the upper water column of the oligotrophic South China Sea” by Yifan Ma et al.

Yifan Ma¹, Kuanbo Zhou¹. Weifang Chen¹, Junhui Chen¹, Jin-Yu Terence Yang¹ & Minhan Dai¹

¹State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, 361102, China

Correspondence to: Minhan Dai (mdai@xmu.edu.cn)

Anonymous Referee #2

The article submitted by Ma et al investigates carbon export from the euphotic layer of the South China Sea, considering two layers (nutricline and euphotic layers). Carbon exports were calculated based on ²³⁴Th particulate fluxes and POC:²³⁴Th ratio. The authors made a complicated discussion on the potential origin of nitrogen sources based on ¹⁵N-isotopic budget. The article is rather difficult to follow as the description of the dataset is not clear, and the sections are not always in the appropriate order. For example, it is really strange to discuss the impacts on physical transport on ²³⁴Th fluxes, whereas there were several pages where the ²³⁴Th fluxes and derived product were extensively discussed.

[Response]: We appreciate the constructive comments from the reviewer. Our manuscript is being thoroughly revised according to the reviewer’s comments in order to optimize the discussion and the logic flow, and to enhance the readability. To do so, we have made a new table (Table R1) for better describing the dataset being used as suggested by the reviewer. In addition, the discussion of the physical transport on ²³⁴Th flux (section 4.1) will be moved to the methods part, before the ²³⁴Th flux and derived fluxes are discussed.

Table R1: Sampling logs and site information along with the accessed parameters and their utilizations.

Station	Arriving time	Latitude [^oN]	Longitude [^oE]	Bottom depth [m]	Parameters	Data utilizations
Total ²³⁴Th	Trap	Partitioning POC flux estimate	Nutrient source diagnosis
SEATS	2017-06-07 00:06	18	116	3907	√	√	√	√
A1^*	2017-06-11 23:55	16	116	4205	√		√
SS1	2017-06-12 20:08	14	116	4107	√		√
H06	2017-06-20 02:28	14.1	116	4289	√		√
H08	2017-06-20 07:51	13.9	116	4063	√		√
H01	2017-06-20 23:41	14	116.1	4139	√		√
H11	2017-06-21 05:18	14	115.9	4297	√		√
B1	2017-06-22 11:43	14	113	2537	√		√
C1	2017-06-23 04:40	12	113	4313	√		√
A2	2017-06-24 03:05	12	116	4079	√		√
B2	2017-06-24 21:42	14	117	3947	√		√

The dataset: there is a need of a table that presents clearly sampling, which station / when / what was measured (water column, trap). It is indicated that the cruise took place from June, 5 to 27, 2017. But typhoon Merbok occurred the 10th. “before our field campaign”. This needs to be clarified. In case of a typhoon had occurred during sampling, one could expect it had impacted the water column and chemical budget. In addition, how could it be possible to use the described ²³⁴Th model which is a steady-state model

[Response]: Thanks for the advices from the reviewer, and a new table of the sampling information will be included in the MS and is shown above.

Note that we did not conduct samplings before or during the typhoon, thus it is impossible for us to build up a non-steady state (NSS) model for ²³⁴Th flux estimation. However, we reasoned that a SS model is in order in the condition under study as the Chl a concentration was not significantly enhanced under the impact of typhoon as shown by the remote sensing derived 8-day averaged surface Chl a (Figure R1). Indeed, the SS ²³⁴Th fluxes remained pretty low, mostly <800 dpm m^-2d^-1 during our study, suggesting that again, export was not much beyond steady state as shown in many prior studies (e.g., Resplandy et al., 2012; Savoye et al., 2006). Additional justification of the SS model will be added during the revision.

Figure R1: Satellite-derived the 8-day averaged surface Chl a in the SCS basin during June 2017, showing that sea surface Chl a concentration was little enhanced during our ship-based sampling period. Note that Station A1 was visited after typhoon Merbok, which was generated on June 9, 2017 at 13.1^oN, 119.8^oE in the southern China Sea. Merbok landed on June 12 at 27.5^oN, 117.3^oE.

Four stations (H01, H06, H08, H11) were sampled around SS1 to check the spatial variability of ²³⁴Th. But it is indicated later that the mega station SS1 was revisited during August 2019 (after a second typhoon Mun, July, 1th) with trap deployment. A clarification must then to be made on what was sampled / when / where.

[Response]: We apologize that we were not clear enough in describing the multiple events happened prior to and post our sampling campaign. We have now included such information in the Table R1 with clarifications throughout the revised MS. Note that our ship-based sampling occurred from June 5^th to June 27^th, 2017 with samplings at station SS1 and its surrounding stations (H01, H06, H08 and H11) on June 12^th, 2017 We did deploy sediment traps at Station SS1 but unfortunately, the traps were not retrieved. We thus used a trap results deployed two years later on July 13^th, 2019 From Station SS1. It must be pointed out that the data accessed from sediment traps deployed at Station SS1 in 2019 was only utilized to evaluate the contribution of subsurface nutrient by δ¹⁵N_PN.

High resolutions profiles: the authors made a great announcement about high resolution profiles. In fact, there are only two, t detailed profiles: SEAT and SS1. The other profiles have a less resolution, and, except for the lower total ²³⁴Th values at about 25 meters at station A1, the profiles of total ²³⁴Th are not so different. It would be interesting that the authors reduce the depth resolution of the SEATS and SS1 profiles to compare the estimated ²³⁴Th.

[Response]: The reviewer is right that the 10-m vertical interval samplings were only conducted at stations SEATS and SS1. We will clarify this in our revision. Following suggestions, we estimated²³⁴Th fluxes at the Ez base by reducing the vertical resolution to a 25-m interval, being 490±60 and 655±71 dpm m^-2 d^-1 respectively for station SEATS and SS1 compared to 522±43 and 631±48 dpm m^-2 d^-1 under the high-resolution sampling mode. The low-resolution sampling thus might induce a less than 6% of uncertainty for the ²³⁴Th flux. However, the high-resolution sampling is essential in order to examine the partitioning of carbon export in the upper water column, especially for the oligotrophic ocean characteristic of the low export flux. Based on high-resolution total ²³⁴Th pattern at stations SEATS and SS1, we first determined ²³⁴Th deficit in the NDL, showing the substantial particle scavenging and POC export at the NDL base at both stations, and we subsequently found similar pattern at the rest of stations and estimated the partitioning in POC export flux between two layers. The reduced sampling resolution might introduce some additional uncertainty to estimates of ²³⁴Th flux and ²³⁴Th-derived POC export flux, but would not change our main conclusion that the base of NDL is the hotspot for particle scavenging and POC export. We will include the above clarification and reasoning in our revision.

Export model: from equation (2), the authors need to produce the two equations relative to the export estimate for the NDL- and NRL-layers, respectively. Use directly the symbol for Fndl and Fnrl. There is no need to use layer i /i-1, that only complicate the model presentation. Also from Fig 2, it seems that calculations are done for each box, but from the text it is less clear that the fluxes from NRL-layer is calculated considering only the lower box or the whole water column above the euphotic layer limit. Figure 2 needs also to be improved: if total ²³⁴Th activities are related to U activities, what means ‘absorb particles, total TH already includes particulate phase. The figure needs to be corrected.

[Response]: We agree with the reviewer’s comments for the Figure 2. We actually calculated ²³⁴Th flux at the export horizons of NDL base and the euphotic zone (Ez) bottom, with the integration carried out between 0-NDL base and 0-Ez bottom (not the lower box as mentioned by the reviewer). Here we use symbol F_NDL and F_Ez as suggested by the reviewer. In order to make the statement clearer, we will revise the main text to emphasize that the flux at the Ez bottom is integrated from the whole box from surface to the Ez bottom.

The reviewer is also right that we only measured total ²³⁴Th activities during the cruises, and we will delete the “particles” in the figure and change “A^dissolved” into “A^total” as suggested by the reviewer (see the details in Figure R2).

Figure R2: Schematic of the ²³⁴Th model under the two-layer nutrient structure. All terms are defined in Equations (2)-(6).

The conversion of ²³⁴Th particulate fluxes in POC fluxes: the conversion is done using the POC/²³⁴Th. The recommendation is to use the large particle ratio. In this work, the authors use the ratio obtained from bottle waters, that correspond to fine particles. The authors need to better argument the choice. The comparison with the trap ratio seems to be biased as trap was done in summer, no during the same sampling cruise. The authors need to be clearer on this aspect. If confirmed, it means that some paragraphs are not justified.

[Response]: Bottle filtration and trap deployment for POC/²³⁴Th were done at Station SEATS during the same cruise (See Table R1). Bottle-derived POC/²³⁴Th ratios at the depth of 50 m and 100 m were respectively 4.4±0.6 and 3.8±0.3 mmol C dpm^-1 compared to 4.4±0.6 and 3.2±0.4 mmol C dpm^-1 from trap samples. We thus confirmed that bottle-derived POC/²³⁴Th was comparable with those derived from trap samples during this cruise. This is consistent with what Zhou et al. (2020) found showing that POC export fluxes based on bottle POC/²³⁴Th was comparable with trap POC fluxes measured before. More importantly, it was impossible to deploy sediment traps at all stations due to practical reasons. For consistency with prior studies in the region (e.g., Cai et al., 2008; Zhou et al., 2013; Cai et al., 2015; Zhou et al., 2020), we primarily used bottle derived POC/²³⁴Th in estimating POC export fluxes as we routinely did in our prior work.

Th/POC flux estimates: most of the article is based on fluxes, but the authors treated data as it was rather instantaneous fluxes, which is clearly not the case. Considering the half-life of ²³⁴Th, a deficit of ²³⁴Th in the water column represent a flux story of several weeks. The only way to have more “instantaneous” fluxes is to repeat profiles at the same station which was not done here. Therefore, it is the main problem with the article. The authors discussed a lot fluxes and potential nutrient sources, but the errors on the fluxes estimate do not support the discussion. There is an over-interpretation of the dataset and the derived fluxes to support the hypothesis of the authors.

[Response]: We completely agree with the reviewer that ²³⁴Th-derived POC export flux is not instantaneous but with a timescale of weeks to months, and understand the reviewer’s concern on the potential issues associated with the correlation between “instantaneous” nutrient and time integrated POC flux. In order to match the time scale between nutrient and POC fluxes, we also correlated ²³⁴Th-derived POC flux with the model-derived monthly average of nutrients during summer (Figure R3, Du et al., 2021). The correlation in between is indeed statistically significant (P<0.05). This suggests that under the oligotrophic condition of the present study, the euphotic layer characterized by low biological productivity, and the system under study is pretty much under steady state. The overall low ²³⁴Th flux as we explained in our above responses to the reviewer, also supports this notion. In addition, we examined the δ¹⁵N_PN value measured in several previous studies in the region (e.g., Kao et al., 2012; Yang et al., 2017; Yang et al., 2022). Taken together, we contend that the conclusion of the subsurface nutrient supported largely is a well plausible interpretation of the dataset. Having said, we will fully consider the comments from the reviewer and revise our MS accordingly.

Figure R3: Relationship between POC export fluxes at the NDL base (black dots) and Ez base (grey dots) vs. the model-derived depth of the top of the nutricline (top) and DIN concentration in the subsurface water at 100 m (bottom).

Others comments: most figures need to be improved and some data combined differently. What is the interest of figure 3?

[Response]: Thanks for the comments, we have revised the figures based on the suggestion above from the reviewer. As our figure 4 has shown the vertical profiles of T and S, here we deleted the figure 3 to simplify the discussion.

References

Cai, P. H., M. H. Dai, W. F. Chen, T. T. Tang, and K. B. Zhou: On the importance of the decay of ²³⁴Th in determining size-fractionated C/²³⁴Th ratio on marine particles, Geophys Res Lett, 33, 23, 10.1029/2006gl027792, 2006.

Cai, P. H., W. F. Chen, M. H. Dai, Z. W. Wan, D. X. Wang, Q. Li, T. T. Tang, and D. W. Lv: A high-resolution study of particle export in the southern South China Sea based on ²³⁴Th : ²³⁸U disequilibrium, J Geophys Res-Oceans, 113, C04019, 10.1029/2007jc004268, 2008.

Du, C. J., R. Y. He, Z. Y. Liu, T. Huang, L. F. Wang, Z. W. Yuan, Y. P. Xu, Z. Wang, and M. H. Dai: Climatology of nutrient distributions in the South China Sea based on a large data set derived from a new algorithm, Prog Oceanogr, 195, 102586, 10.1016/j.pocean.2021.102586, 2021.

Kao, S. J., Terence Yang, J. Y., Liu, K. K., Dai, M., Chou, W. C., Lin, H. L., Ren, H.: Isotope constraints on particulate nitrogen source and dynamics in the upper water column of the oligotrophic South China Sea. Global Biogeochem Cycles, 26: GB2033, 10.1029/2011GB004091, 2012.

Resplandy, L., Martin, A. P., Le Moigne, F., Martin, P., Aquilina, A., Mémery, L., Lévy, M. and Sanders, R.: How does dynamical spatial variability impact ²³⁴Th-derived estimates of organic export? Deep Sea Research Part I, 68: 24-45, doi: 10.1016/j.dsr.2012.05.015, 2012.

Savoye, N., C. Benitez-Nelson, A. B. Burd, J. K. Cochran, M. Charette, K. O. Buesseler, G. A. Jackson, M. Roy-Barman, S. Schmidt, and M. Elskens: ²³⁴Th sorption and export models in the water column: A review, Mar Chem, 100, 234-249, 10.1016/j.marchem.2005.10.014, 2006.

Yang, J. Y. T., Kao, S. J., Dai, M., Yan, X., Lin, H. L.: Examining N cycling in the northern South China Sea from N isotopic signals in nitrate and particulate phases. J Geophys Res-Biogeoscience, 122: 2118-2136, 10.1002/2016JG003618, 2017.

Yang, J. Y. T., Tang, J. M., Kang, S., Dai, M., Kao, S. J., Yan, X., Xu, M. N., Du, C.: Comparison of nitrate isotopes between the South China Sea and western North Pacific Ocean: Insights into biogeochemical signals and water exchange. J Geophys Res-Oceans, 127: e2021JC018304, 10.1029/2021JC018304, 2022.

Zhou, K. B., M. H. Dai, S. J. Kao, L. Wang, P. Xiu, F. Chai, J. W. Tian, and Y. Liu: Apparent enhancement of ²³⁴Th-based particle export associated with anticyclonic eddies, Earth Planet Sc Lett, 381, 198-209, 10.1016/j.epsl.2013.07.039, 2013.

Citation: https://doi.org/10.5194/bg-2022-196-AC2

AC4: 'Reply on RC2', Minhan Dai, 20 Jan 2023

The comment was uploaded in the form of a supplement: https://bg.copernicus.org/preprints/bg-2022-196/bg-2022-196-AC4-supplement.pdf

Citation: https://doi.org/10.5194/bg-2022-196-AC4

Yifan Ma et al.

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Yifan Ma et al.

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Short summary

We distinguished particulate organic carbon (POC) export fluxes out of the nutrient-depleted layer (NDL) and the euphotic zone. The amount of POC export flux at the NDL base suggests that the NDL could be hotspots of particle export. The substantial POC export flux at the NDL base challenges traditional concepts that the NDL was limited for POC export. The dominant nutrient source for POC export fluxes should be subsurface nutrients which was determined by ¹⁵N isotopic mass balance.


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