the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Nov 2024
Pelagic coccolithophore production and dissolution and their impacts on particulate inorganic carbon cycling in the western North Pacific
Abstract. Coccolithophores, a type of single-celled phytoplankton that is abundant in global oceans, are closely associated with the carbonate pump and thus play a crucial role in the marine carbon cycle. Here we investigated coccolithophore abundances, species compositions, coccolithophore calcium carbonate (CaCO3 as calcite) and particulate inorganic carbon (PIC) concentrations in the upper water column of the western North Pacific Ocean, along a meridional transect spanning the oligotrophic subtropical gyre and the nutrient-richer Kuroshio-Oyashio transition region. Our results revealed that Umbellosphaera tenuis was the dominant coccolithophore species in the former, while Emiliania huxleyi and Syracosphaera spp. dominated in the latter. Coccolithophore calcite contributed a major fraction of the PIC standing stocks above a depth of 150 m, among which E. huxleyi was the most important producer while less abundant and larger species also played a role. The coccolithophore CaCO3 production rate in the subtropical gyre (0.62 mol m−2 yr−1) was ~5-fold higher than that in the Kuroshio-Oyashio transition region (0.14 mol m−2 yr−1), indicating that inorganic carbon metabolism driven by coccolithophores is relatively strong in oligotrophic ocean waters. Using a box model including coccolithophore CaCO3 production and metabolic calcite saturation state, we demonstrated that CaCO3 dissolution associated with organic carbon metabolism can generate excess alkalinity in the oversaturated upper water column of the western North Pacific Ocean. Results of our study highlight the critical role of coccolithophores in CaCO3 production and dissolution; knowledge of these processes is important to assess PIC cycling and carbonate pump efficiency in the pelagic ocean.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-3492', Alex Poulton, 20 Dec 2024
GENERAL COMMENTS
The article by Han et al. represents a considerable amount of work and presents a wide-ranging number of details in terms of coccolithophore species composition, species-specific PIC concentrations, size-fractionated PIC concentrations, PIC standing stocks, estimates of CaCO3 production related to coccolithophores, statistical exploration of environmental drives of coccolithophore abundance, PIC and species composition, and an exploration of whether metabolically driven dissolution in microenvironments in sinking aggregates can explain shallow dissolution of CaCO3. This extensive list highlights that there is just too much in this single paper and its considerable breadth results in significant missing sections on methods (i.e. all the environmental data) and a full exploration of the limitations of the scaling, statistics and estimates made. A recommended step forward would be to vastly simplify the paper (e.g., focus on coccolithophore species, PIC and CaCO3 production) to allow room to fully discuss the results and insights presented.
That no methodology for the environmental data (nutrients, carbonate chemistry) is included leads to significant issues and concerns over the quality of this data. These are parameters for which there are important international norms to ensure data quality (e.g., use of internal standards, CRMS, measures of precision and replication) and so details need to be included. Further, the data availability statement only leads to a general landing page for the data rather than more direct links to the individual datasets included (e.g., coccolithophore count data, environmental data, hydrographic data). This is not to say there is anything amiss of the data and is clearly a result of the shear breadth of other material included.
Moreover, there are some confusing trends in the article, one of which is the swopping of units (from mol to g and back again), and no clear statement of what elements the units are in fact presenting (C or CaCO3). It took several readings of the paper and associated references to realise that all the mass units (mg, g) are in mg/g of CaCO3 rather than C. It would have been good to have this pointed out early in the manuscript – and sticking to either grams or moles throughout would also have eased the reading and interpretation of the paper.
As well as the missing methods there are also some examples of limited discussion where there is not room in the article to fully explore the scientific and methodological issues raised in a suitable way to allow the reader to understand the results. Several examples of this exist, most importantly: (1) the conversion of cell counts to cell CaCO3 is not a trivial conversion and a more thorough exploration of the possible errors and limitations of these methods should be included; (2) there is no explanation of whether the authors consider 150 m to be a consistent euphotic zone depth across the transect and how integrations to this depth impacts on the research questions asked and conclusions of the paper; (3) the conversion of cell CaCO3 into CaCO3 production involves numerous assumptions and room should be made to present the resulting growth rates from these estimates, and comparison of these with in situ estimates of growth rates and other more direct measurements of CaCO3 production (e.g., Daniels et al., 2018); (4) the three different statistical analysis of coccolithophore trends with environmental data (RDA, correlation, random forest) are presented and summarised in 2 paragraphs of the discussion, which barely allows any setting of the results in the context of coccolithophore ecology; (5) the modelling approach to examine whether metabolic respiration drives CaCO3 dissolution in sinking particles has numerous inherent assumptions and completely ignores the potential role of zooplankton ingestion and digestion.
This last example includes some of the strongest examples of limited discussion, where some of the literature cited makes much more nuanced (or even opposite) conclusions about the relative roles of micro-environment and zooplankton led dissolution. This is an active research field and so the authors must fully discuss the different mechanisms proposed, especially if they are going to conclude that ‘our results indicate that shallow-water CaCO3 dissolution indeed occurs in the western North Pacific Ocean mainly as a result of metabolic acidification in the particulate microenvironment’ (Lns 416-417). Are the authors confident that their model results could not also be interpreted as dissolution in zooplankton guts (i.e. another microenvironment) and that their approach accurately compares both proposed mechanisms of dissolution? This section of the discussion also brings in several totally new concepts (Lns 411-414: Alk*, TA*, CFC age-based RTA, ALK*-transit time distribution, 14C-age based RTA values) to the paper with no background to their meaning, interpretation or limitations which is completely confusing at this (late) stage of the article.
There is considerable merit to the work done by Han et al., however a single paper does not do justice to the data collected or its interpretation, or the serious limitations and assumptions included in the methods employed. Given the missing methods on the environmental data and the brevity with which the results are discussed, it is difficult to fairly assess the work presented.
SPECIFIC COMMENTS
Ln 1 (Title), Coccolithophores are only pelagic (not benthic) so suggest removing pelagic from the title. Also see general comments on content of the paper and consider what has been directly measured (cell counts, PIC) and what has only been estimated (production, dissolution).
Ln 15, When describing a species as dominant, especially in light of the various metrics used in the paper, does this refer to numerical dominance?
Ln 17, Is E huxleyi the most important producer or contributor to the PIC standing stocks? High standing stocks along the sample transect does not necessary equate to CaCO3 production rates as growth rates between species vary and it is not clear if this statement includes detached coccoliths or not.
Ln 18-19, It is strange to present the annual integrals in the abstract rather than the daily rates estimated to be associated with the observations collected. There are a lot of limitations and caveats to go from PIC concentration to growth rate, let alone to scale these to annual rates.
Ln 19-20, What does the line ‘inorganic carbon metabolism driven by coccolithophores is relatively strong in oligotrophic ocean waters’ mean? Its meaning is vague and relatively strong (relative to where?) is not a quantitative term.
Ln 27, Surely CaCO3 production and dissolution are THE two processes associated with CaCO3 cycling; the phrasing here implies that there are other processes involved. Also, it is not the ‘so-called’ carbonate pump, this is what it is called (Ln 28).
Ln 33, This line does not follow (‘this acidification feedback mechanism’) the previous line or make sense. This might also be a good point to introduce carbonate chemistry and would help the reader.
Ln 40, Contrast this line (‘a major fraction’) with the values given in the preceding lines. Please give a value.
Ln 41, What is a ‘data assessment’? Surely the Ziveri et al. (2023) paper is based on observations?
Ln 43, This line (about large uncertainties) should link to the preceding line as there are large uncertainties in the composition of CaCO3 production between the different pelagic groups mentioned in line 42.
Ln 45, Daniels et al. (2018) is not listed in the references. Also, why are the values on Ln 46 in mg m-2 d-1 rather than mol (as in the abstract)? It should also be made very clear that the values given throughout the paper are in CaCO3 (i.e. mol/g = 100). Are the other values in the paper (PIC, CaCO3 production) given in CaCO3 or C?
Lns 48-49, Unnecessary repetition (‘along with the current scarcity of studies’).
Ln 50, This is a bold statement (‘CaCO3 dissolution is generally assumed to mainly occur below the saturation horizon’), especially based on the multiple references included in the article and that shallow dissolution has been recognised since the 1990s (e.g., Milliman e al., 1999 Deep-Sea Research) – this statement should have a reference or be modified.
Ln 57-58, See new paper by Oehlert et al., 2024 (GBC, doi: 10.1029/2024GB008176) arguing that high-Mg fish calcites have a very low PIC:POC and the POC associated with fish faecal pellets provides considerable protection as they rapidly sink.
Ln 59-60, Please expand on this issue in light of: Mayers et al. (2020, doi: 10.3389/fmars.2020.569896) and Dean et al. (2024, doi: 10.1126/sciadv.adr5453) which imply that (micro)zooplankton grazing can be an important loss process for coccolithophore CaCO3.
Ln 62-65, Please consider shortening and simplifying this sentence.
Ln 65-66, Do these differences highlight deep CaCO3 production, or that the CaCO3 production is happening over a deeper euphotic zone?
Ln 66-68, This line needs the relevant citations.
Ln 69, coccolithophore should be coccolithophores.
Lns 74-76, There appears to be 4 research questions here, with (3) split into whether there is shallow dissolution, and a fourth on whether this is driven by metabolic activity. Further, while research questions (1) and (2) are clearly addressed by the data presented in the article, (3) and (4) are based on the addition of modelling to the discussion (see later comments) and it is unclear if these are addressed in the depth that they deserve.
Ln 89, Figure 1 – The colour bar used means that there are two bands of yellow (one around 0.75 and one at the maximum value), which is confusing. Also, the precise dates for the composites are not included (are these 1-30th June)?
Ln 99, Based on the use of ‘filters’ in the next line of the method (‘filters were oven-dried’) suggest adding membrane filters to the preceding line to avoid confusion – unless the SEM filters weren’t dried and stored in petri-slides?
Ln 103, Does large and small fractions of PIC need a unique abbreviation, or could they just be referred to as small and large? There use (and non-use at times) in the article is confusing. Also, does PICtotal need an abbreviation, or could it just be referred to as total PIC?
Ln 110, Do the authors mean the analytical precision was <10%? The use of ‘better than’ is confusing.
Ln 112, Phrasing confusing – sounds like only some of the filters collected were mounted, do the authors mean a portion of of the filters was mounted?
Ln 120-121, Have the authors seen the article by Sheward et al. (2024, doi: 10.1038/s41597-024-03544-1)? A comparison between the cell PIC values in these articles would be a valuable addition to the literature. As the scaling from cells to cell PIC is key to this article, some comments around potential sources of error and limitations (e.g., accurately assessing the number of coccoliths) should be included. Also, ‘all the’ is unnecessary in the second line.
Ln 124, Do the authors mean shallower than 150 m or deeper (i.e. above) 150 m? Also, why 150 m? This is unlikely to be the euphotic depth across the entire transect.
Ln 125-126, Why are the turnover times and division rates given here different than from Ziveri et al. (2024)? What were the growth rates that resulted from these estimates? What are the potential sources of error and uncertainty with this method of estimating CaCO3 production?
Ln 134, No methods are included for the environmental conditions. Much more details are needed for these parameters, such as detailed methods including internal standards, precision estimates, and CRMs. These are all included as standard with the environmental data and as presented as such there is little confidence in the quality of the environmental data as this cannot be assessed as part of the review. As these are key to the following sections of the manuscript and the calculations made, they must be presented in detail here.
Ln 142, Why is only the effect of microenvironment undersaturation considered? Would the same configuration describe dissolution driven by metabolic activity inside zooplankton guts? Surely to test the dominant driver of CaCO3 dissolution, all potential drivers need to be considered? On Ln 143, the assumption that aerobic metabolic activity consumes all ambient oxygen is a significant assumption – do the sub-surface waters go anoxic or are the authors suggesting that internal environments in sinking marine snow are anoxic? If the authors remove this assumption, can they still get these patterns of dissolution?
Ln 166, Do the authors mean nutricline, as related to multiple nutrients, or the nitracline, as related to nitrate. As the authors describe this in terms of nitrate, this seems to be the nitracline. Following on from this (Ln 175), why was the depth where DIN reached 0.1 umol/L used rather than (as more commonly used) 1 umol/L? Was this something to do with the detection limits of the measurements, in that 0.1 umol/L is a common threshold for nitrate+nitrite detection and so this effectively describes the first depth where nitrate was detectable? Without the detailed methods on the environmental parameters, it is difficult to assess this criterion. Finally, why is this depth not plotted on Figure 2?
Ln 171, What is the justification for using 0.03 mg m-3 to define the transition in density at the base of the mixed layer? The authors should give a reference as there are multiple criteria and methods used to define the mixed layer. Also, did the mixed layer depth vary by 11-25 m around a value, or do they mean that the mixed layer varied from 11 to 25 m in depth? How does this compare with their assumption of a 150 m euphotic zone depth?
Ln 181, Figure 2 – The authors should be wary of using ODV with sparse data as it tends to expand data beyond the sample depths with a horizontal bias (kms) rather than vertical (ms) one and creates (sometimes fictional) patterns. These can be seen clearly in this Figure; for example, the DCM (e) is at ~70 m at 35oN, but there are no samples to confirm that, PIC is stretched around 40oN both N and S at a depth of around 30 m but there are no sample points to support this pattern. Similar comments can be made with panels (g) and (f). As these are key parameters for the paper, the authors should consider different ways of plotting the data that more accurately represent the patterns and spatial limitations of the data.
Ln 187, How much of the apparent pattern of low PIC in the surface and increasing with depth is driven by the contouring in Figure 2? In Figure 3 why are no error bars included to give an idea of the relative patterns? Also, in terms of Figure 3, why are the three sets of measurements at different depths - they do not line up? How does this impact the interpretation of the data?
Ln 192, In the methods section (Ln 118) the detection limits for coccolithophore cell counts from SEM is given as 1.87 cells mL-1, but line 192 reports cell concentrations of 0.97 cells mL-1 (=970 L-1)? Please explain this discrepancy.
Ln 196, Here the authors talk about averages, but the preceding lines gave specific concentrations, and it is not clear what this value for coccoliths is for – all depths, all stations? As the difference between subtropical and subpolar waters is a strong theme of the paper wouldn’t it make sense to compare the averages for these?
Ln 211, What does predominantly mean when used here – do these refer to coccosphere abundances?
Ln 213, Do all species listed in lines 211 to 213 compromise >1% of total coccosphere abundance or just F profunda?
Ln 216, Did E huxleyi contribute the largest fraction in every sample?
Ln 219, What is the lower euphotic zone (LPZ) and how are coccolithophore species assigned to this depth? Is there a missing reference here?
Ln 225, Figure 4 – Beyond E huxleyi there is very little detail visible in this plot, could the authors present this as percentage contributions rather than cell abundances? Do the authors want to emphasise abundance or species diversity in this figure?
Ln 229, Is the coccolithophore CaCO3 really 0.00 umol L-1 or <0.01 umol L-1?
Ln 234, Why are exact numbers or ‘ca.’ given elsewhere in the article but “~” is used here to indicate approximately?
Ln 238, Figure 5 – What does this show? Are these averages for the all stations, all depths? How does this add to the theme of the paper in terms of latitudinal or vertical differences? Being Pie Charts this automatically presents percentage contributions, so if these are averages then there is no option to show error bars and compare the different components. Is this the best way to present the data or compare sampling depths/regions?
Ln 234, Does this mean the measurements were integrated from the surface depth to 150 m? What was the argument for 150 m (in view of changes in the euphotic zone depth)? How shallow were the shallow depths and were they consistent? Would it not be more consistent to assume that the unsampled surface depth was the same as the shallowest sampled depth?
Lns 244 onwards, Are these concentrations in mg CaCO3 m-2 or mg C m-2? Are they averages for the different areas, and if so, what are the standard deviations?
Ln 243, Figure 6 – This is a very difficult figure to understand. (a) Why are area averages given now whereas elsewhere in the paper the latitudinal pattern is emphasised? Where are the error bars for the averages? Is the data normally distributed? Why is the coccolithophore contributions surrounded by orange? Are the average bottle and sum of small and large (note no abbreviation of SSF and LSF are used) significant the same when compared? (b) The data here is obviously not normally distributed and generally the estimates of CaCO3 production tend towards lower values – however (!) the blue diamonds, which are not defined in the legend and so are we to assume they are averages, are offset higher than the data is distributed. This looks to be an example of where a geometric mean should be used, and the values should be lower than the blue diamonds – indicating that the authors are overestimating CaCO3 production at the different stations. Please explain.
Ln 258, This is the first mention of in situ pump data since the methods and so is slightly confusing in terms of SSF and LSF (small and large PIC particles). Also, are the values here mg CaCO3 m-2?
Lns 262-263, Not clear at all as to how the CaCO3 production rates presented here follow from the statement about turnover times. Would it not make sense to present the growth rates that derive from the estimates of CaCO3 production and compare these with measured growth rates in the open ocean? Are the growth rates estimated similar between the two different regions and thus the differences (or similarities) driven purely by the standing stocks of PIC? What would clarify this would be to present in Figure 6 the integrated PIC for all the stations, the growth rates estimated for each station and the CaCO3 production – this way, the reader can follow how the three interact.
Ln 267, On lines 265 to 266 the link between high CaCO3 production and high cell numbers is established, whereas the comparative information is not given in Ln 267; does the lowest CaCO3 production correspond to the lowest cell counts?
Lns 271-278, All this material appears to be introductory material and is a repeat of what has been said in the introduction.
Ln 282, The authors should consider citing Poulton et al. (2017, doi: 10.1016/j.pocean.2017.01.003) alongside Balch et al. (2019) in terms of defining depth flora in the subtropics.
Lns 282-285, Statements around coccolithophore nutrient stress and cell quotas are best backed up by physiological references, not modelling references.
Ln 288, O’brien et al. should have a capital; O’Brien et al., 2016.
Lns 292-296, It is impossible to assess the RDA without details of the methods for the environmental data and some statements around whether the authors checked for autocorrelations between the different variables. Also, what is the justification for putting in some variables, for example latitude or depth? Latitude should correlate with temperature and is depth supposed to represent a pressure effect or light availability. It would be good to see some mechanistic physiological exploration of how the variables included in the RDA impact on coccolithophore growth (as this underpins the CaCO3 production estimated). Are all the variables included necessary? This also goes for the Spearman comparison. In general, there is so little discussion of this in the discussion that this analysis comes across as very superficial (13 lines) despite including three different statistical tests of the data that are not found in the results.
Lns 325-327, The authors need to expand on their reasoning here – how do relationships between coccolith and coccosphere concentrations indicate that the detached coccoliths came from living cells and where not (e.g.) advected into the area, from viral lysis of cells or disintegration of the coccospheres after grazing or from faecal pellets or programmed cell death?
Ln 329, Figure 8 – These plots miss the sample number for the different species and it is surprising that despite the variability in presented sample number and data distribution, the p values for all the plots are p<0.01. Are these plots all forced through zero?
Ln 333, This is the first mention of aggregates in the text. The authors need to expand on this and explain how they were measured/identified/classified etc.
Ln 336, How does the statement of the role of large species link to the results presented in the article? Do the authors see these species, and do they make large contributions? Same comment on lns 337-339.
Ln 341, Is not the point being made before that large, rare species can play important roles on CaCO3 production and export? Based on the preceding references (e.g., Daniels et al., 2016) and comments this seems to better follow.
Ln 347-348, Why do the authors consider that ‘CaCO3 is largely produced in the lower layer of the euphotic zone’ when calcification is a light-dependent process? Is this what is seen in other studies of CaCO3 production (e.g., Daniels et al., 2018). References are needed here, and this should be expanded as it is a (potentially) important point. Or, do the authors mean that CaCO3 production occurs over a significant portion of the euphotic zone and not just the surface? As the authors did no measure CaCO3 production, how does this relate to their results?
Ln 353, Is ‘flux’ the correct term in this line? Do the authors mean that subsurface coccolithophore CaCO3 contributed significantly to the total water column PIC? Where does the flux relate to this?
Ln 354, Is this what the authors observed in their data – i.e. large and PIC heavy species in the subtropical gyre?
Lns 356-358, The final statement is confusing – why would low surface PIC values imply that coccolithophore CaCO3 production over the whole water column is not important?
Ln 360, Are the values in this line averages? What are the standard deviations and are these values significantly different?
Ln 361, Is the LSF PIC mentioned here from this study or Ziveri et al. (2023)?
Ln 363-366, These lines need to be better related to the results presented, here they just appear as statements without the context of the present study.
Lns 368-371, This is a large leap here from discussions of pelagic calcifiers and different groups, to how ecosystem structure impacts the relative importance of different calcifiers – for example there are no data or statements in terms of other phytoplankton groups and the nutrients they are dependent on, the availability of prey for heterotrophic calcifiers, etc. This statement needs far more background and justification. No abundances of non-calcareous phytoplankton are given or attempts to estimate the amount of the phytoplankton community that coccolithophores represent, or how these changes between sites.
Ln 375, Figure 9 – It is not possible to see all the Pie Charts of the data from the present study so represents a poor figure trying to compare studies. Also, how do the authors know that the <51 um fraction is only coccolithophores and (e.g.) not shell fragments of foraminifera?
Ln 381, As the title of the paper is around CaCO3 production it is surprising to see that only two paragraphs of the discussion cover this subject – it seems rather a light touch for a key parameter of the paper. Have the authors considered comparing their measurements with other sources of rate data (e.g., Daniels et al., 2018) or estimates of coccolithophore growth rates in the ocean?
Ln 383-384, Can the authors check the values given from Balch et al. (2007) and Hopkins and Balch (2018) as we cannot find these area specific rates in either publication, both deal with global PIC production using slightly different (but related) physiological-based models.
Lns 390-392, Does this statement relate to the data presented in this article? If so then it is a concern and considerably more should be said as to possible sources of these errors and inconsistencies (e.g., scaling from cell numbers to PIC concentrations).
Ln 399, Do the authors consider 150 m to be the euphotic zone along the entire transect? This seems highly unlikely due to the changes in vertical distribution of the phytoplankton community (i.e. Chl-a). Some statements are needed in the article about what 150 m represents and what the authors consider in terms of the difference (or not) between the euphotic zone depth and 150 m.
Ln 404-406, How did the authors do a one-way ANOVA on PIC distribution patterns? More needs to be said or shown in terms of what data has been compared and how the authors consider different water parcels or hydrographic regions. This seems a rather throw away comment that needs far more background; it would not be normally expected that an ANOVA on hydrographic data distributions is a valid statistical approach.
Ln 409, This is a significant assumption (that 100% of coccolithophore production is exported out of the euphotic zone) and needs far more discussion, including references and exploration of how if this was wrong it would impact on the article’s conclusions. Recognising that coccolithophores could be heavily grazed by microzooplankton (Mayers et al., 2019, Dean et al., 2024) and are prone to significant levels of viral infection and lysis (e.g., Vincent et al., 2023, doi: 10.1038/s41467-023-36049-3) severely questions how valid this assumption is.
Lns 412 and 414, Introducing totally new concepts (TA*-CFC age-based RTA, Alk*-TTD 14C age based-RTA) at this (late) stage of the article (i.e., concepts not mentioned in the introduction) makes this section of the discussion very confusing and difficult to follow. That these important points are only covered in 4 lines also leaves little room to fully explore them.
Lns 416-417, Is this self-validation? If the model did not assume that all production is exported (c.f. POC production), that all oxygen is consumed and that marine snow or faecal pellet sinking speeds are unlikely to be as slow as 10 m d-1, what conclusions do this lead to? Do the authors have data to support the assumptions (e.g., amount of CaCO3 production exported, characteristics of sinking particles in terms of marine snow or faecal pellets, sinking speeds, oxygen gradients in porous marine snow) in the model that validates them? Could their result be interpreted in a different way if CaCO3 dissolution occurs via the metabolic activity of zooplankton? Does their model rule out grazing as a contributor to CaCO3 dissolution or does it just assume that it doesn’t occur?
Ln 420, Figure 10 – Panel (a) is relatively easy to see, though it would be good to see an exploration of sinking speeds between 10 and 100 m d-1 (e.g., 50, 75 m) and some comparison with the literature on particulate sinking speeds of marine snow and fecal pellets (e.g., see Jansen et al., 2002 who conclude ‘respiration-driven dissolution of calcite in the water column seems to be unlikely .. as the size, settling velocity and porosity of marine snow aggregates are unfavourable for creating a microenvironment with gradients sufficient to convert an oversaturated bulk environment into a locally undersaturated state.’). Please include more discussion of the factors involved than citing only one side of the debate (e.g., Jansen and Wolf-Gladrow, 2001). However, note that Jansen and Wolf-Gladrow (2001) conclude that ‘up to 70% of the ingested carbonate maybe be dissolved in the guts’ in non-bloom situations – could the authors explain where the 25% in line 437 is from? Panel (b) is extremely difficult to understand, for example why are the depths now in density and how does this relate to panel (a) are the densities for the other points the same, how do the lines where no data points included relate in depth to the discrete measurements?
Ln 430, Subhas et al (2022) do not fully agree with the present study; instead finding that ‘a combination of dissolution due to zooplankton grazing and microbial aerobic respiration within degrading particle aggregates’ lead to shallow metabolically driven dissolution. Subhas et al. (2022) also point out that the dissolution of high-Mg carbonates is not necessary to drive shallow dissolution. This is not reflected in lines 434-436. Further, the single comment from Jansen and Wolf-Gladrow (2001) does little justice to the existence of multiple dissolution pathways (especially noting as above that this reference concludes that up to 70% of ingested carbonate may be dissolved through zooplankton ingestion).
Ln 452, Data Availability - The authors need to provide a more direct link to the relevant data from the article than the general landing page for the Science Data Bank.
Citation: https://doi.org/10.5194/egusphere-2024-3492-RC1 -
AC2: 'Reply on RC1', Minhan Dai, 10 Feb 2025
Response to reviewers
We thank the reviewers for their detailed comments that helped to significantly improve the manuscript. For your convenience, reviewer comments are presented below in black font, followed by our answers in blue font.
Reviewer #1
General comments
The article by Han et al. represents a considerable amount of work and presents a wide-ranging number of details in terms of coccolithophore species composition, species-specific PIC concentrations, size-fractionated PIC concentrations, PIC standing stocks, estimates of CaCO3 production related to coccolithophores, statistical exploration of environmental drives of coccolithophore abundance, PIC and species composition, and an exploration of whether metabolically driven dissolution in microenvironments in sinking aggregates can explain shallow dissolution of CaCO3. This extensive list highlights that there is just too much in this single paper and its considerable breadth results in significant missing sections on methods (i.e. all the environmental data) and a full exploration of the limitations of the scaling, statistics and estimates made. A recommended step forward would be to vastly simplify the paper (e.g., focus on coccolithophore species, PIC and CaCO3 production) to allow room to fully discuss the results and insights presented.
[Response]: We appreciate the critical and constructive comments from the reviewer in terms of the breadth of the paper and the insufficiency in the descriptions of methods and their uncertainty estimates. In response to your comments/suggestions, we have made the following revisions:
1. Missing sections on methods: The methods related to environmental data, which were previously in the supplementary material, have now been moved into the main text for better accessibility and clarity. Moreover, we have added a detailed description of the morphometric-based calcite estimation method. Regarding the conversion of cell counts to cell CaCO3 and subsequently to CaCO3 production, we have added a discussion addressing the potential errors and limitations of these calculations.
2. Streamlined focus: To highlight the main objectives of the manuscript (coccolithophore species, PIC, and CaCO3 production), we have reorganized the discussion section and removed the original 4.4 section on shallow-water dissolution of CaCO3. An outline of the revised manuscript structure is as follows:
4.1 Contribution of coccolithophore calcite to PIC
4.2 Coccolithophore responses to environmental factors
4.3 CaCO3 production compared with the eastern North Pacific
That no methodology for the environmental data (nutrients, carbonate chemistry) is included leads to significant issues and concerns over the quality of this data. These are parameters for which there are important international norms to ensure data quality (e.g., use of internal standards, CRMS, measures of precision and replication) and so details need to be included. Further, the data availability statement only leads to a general landing page for the data rather than more direct links to the individual datasets included (e.g., coccolithophore count data, environmental data, hydrographic data). This is not to say there is anything amiss of the data and is clearly a result of the shear breadth of other material included.
[Response]: Thank you for your comment regarding the methods description and data availability. The methodology for the environmental data (e.g., Chl a, nutrients and carbonate chemistry), which was previously included in the supplementary material, has now been incorporated into the main text. Additionally, details on the use of internal standards, measures of precision, and replication have been included to ensure transparency and data quality. Please note that we have participated in several inter-calibration experiments, including the IOCCP-JAMSTEC inter-laboratory comparison (https://www.ioccp.org/index.php/more/917-nutrients-references) and the CSIRO-INIV 2023 cruise for nutrients analyses, as well as carbonate chemistry measurements (Bockmon and Dickson, 2015). The quality of our nutrient and carbonate chemistry data has been internationally recognized. We have also published numerous papers based on nutrient and carbonate chemistry data (e.g., Du et al., 2017; Roberts et al., 2021; Zhao et al., 2021; Yuan et al., 2023), further demonstrating the high quality of our data.
We would also like to clarify that the data used in this study have already been made publicly available. As this is an open discussion review, the data link was originally provided in the cover letter to ensure access for reviewers and editors. We have now included the link of https://www.scidb.cn/en/s/i6bMFn in the “Data Availability” section of the revised manuscript for better visibility.
Moreover, there are some confusing trends in the article, one of which is the swopping of units (from mol to g and back again), and no clear statement of what elements the units are in fact presenting (C or CaCO3). It took several readings of the paper and associated references to realise that all the mass units (mg, g) are in mg/g of CaCO3 rather than C. It would have been good to have this pointed out early in the manuscript – and sticking to either grams or moles throughout would also have eased the reading and interpretation of the paper.
[Response]: We apologize for any confusion caused. In the section on standing stock, we initially used mg CaCO3 m−2. To improve clarity and consistency, we have now standardized the units throughout the manuscript. Specifically, standing stocks are expressed in mmol m−2, daily production rates in mmol m−2 d−1, and seasonally corrected annual production rates in mol m−2 yr−1.
As well as the missing methods there are also some examples of limited discussion where there is not room in the article to fully explore the scientific and methodological issues raised in a suitable way to allow the reader to understand the results. Several examples of this exist, most importantly:
(1) the conversion of cell counts to cell CaCO3 is not a trivial conversion and a more thorough exploration of the possible errors and limitations of these methods should be included;
[Response]: Thank you for your comment. We recognize that the conversion of cell counts to cell CaCO3 is not a trivial calculation and have made two specific modifications:
1. Expanded method description: We have expanded the description of the calculation method to provide greater details and clarity as follow.
Individual coccolithophore calcite content was calculated by multiplying the number of coccoliths per cell by the average coccolith calcite mass of a given species. The average coccolith mass was estimated based on coccolith size (usually using coccolith length) and a shape factor related to coccolith cross-sectional shape (Young and Ziveri, 2000).
where is coccolith size (µm), is a species-specific shape constant, and 2.7 is the calcite density (CaCO3; pg µm−3). The specific coccolith distal shield length or process height used in the calculation was measured from SEM images. Measurements were conducted using imageJ free software (imagej.nih.gov/ij/) and Coccobiom2-SEM measuring macro (Young, 2015). The species-specific values used were from Young and Ziveri (2000) and Jin et al. (2016). The number of coccoliths per coccosphere was obtained from Yang and Wei (2003) and Boeckel and Baumann (2008). The calculation of coccolith PIC is detailed in Supplementary Table 2.
Table S2. Coccolith mass estimates of the main coccolithophore species using morphometrics. The species-specific values used were from Young and Ziveri (2000) and Jin et al. (2016). CN, the number of coccoliths per cell, was obtained from Yang and Wei (2003) and Boeckel and Baumann (2008).
Species
Length (µm)
Ks
Mass CaCO3 (pg)
CN
Emiliania huxleyi
3.48±0.22
0.02
2.28
24
Gephyrocapsa ericsonii
2.04±0.21
0.05
1.15
15
Gephyrocapsa oceanica
4.87±0.52
0.05
15.59
23
Discosphaera tubifera
3.67±0.34
0.07
9.34
47
Umbellosphaera tenuis
5.72±0.74
0.015
7.58
25
Umbellosphaera irregularis
5.72±0.74
0.015
7.58
26
Syracosphaera molischii
3.01±0.41
0.03
2.21
38
holo-coccolithophores
4.03±0.25
0.03
5.30
70
Algirosphaera robusta
2.83±0.29
0.06
3.67
32
Florisphaera profunda
3.69±0.71
0.04
5.43
62
Calcidiscus leptoporus
7.35±1.03
0.08
85.77
29
Oolithotus fragilis
7.35±1.03
0.07
75.05
32
Umbilicosphaera sibogae
4.85±0.43
0.05
15.40
68
Helicosphaera carteri
9.87±0.95
0.05
129.80
21
2. Added possible errors and limitations: We have included the discussion of the potential errors and limitations associated with the morphometric-based calcite estimation method.
We acknowledge that this calcite estimation method is subject to significant uncertainties. As described by Young and Ziveri (2000), the combined uncertainties in (shape factor) and coccolith size can result in errors of approximately ±50%. Furthermore, Sheward et al. (2024) have extensively discussed the quantification of uncertainty sources, suggesting that an additional uncertainty of 5–40% may arise from slight variations in and size between coccoliths on the same coccosphere, as well as errors in coccolith number estimation. Additionally, it is important to note that further uncertainties can be introduced by counting inaccuracies, particularly in cases where clumps or overlapping coccoliths are present. Despite these possible errors and limitations, our data offer robust and comparable insights into coccolithophore calcite dynamics.
(2) there is no explanation of whether the authors consider 150 m to be a consistent euphotic zone depth across the transect and how integrations to this depth impacts on the research questions asked and conclusions of the paper;
[Response]: We acknowledge that 150 m does not represent the euphotic zone depth across all stations. Based on your suggestion, we have revised the integration depth from 150 m to the euphotic zone depth as determined by the 0.1% surface photosynthetically active radiation (PAR; Supplementary Table S1). However, this adjustment does not affect the main conclusions. Our results showed that the contribution of coccolithophore calcite to the PIC standing stock is higher in the oligotrophic NPSG region compared to the Kuroshio-Oyashio transition region. This finding is further supported by the size-fractionated PIC results. We have made corresponding adjustments to the relevant sections of the manuscript.
Table S1. Location of the seven sampling stations and their euphotic zone depths during the NORC2022-306 cruise. Stations M30, M32 and M35 were in the North Pacific Subtropical Gyre, and the remaining stations were in the Kuroshio-Oyashio transition region.
Station
Latitude (°N)
Longitude (°E)
Euphotic zone depth (m)
M30
28.5
155
219
M32
30.5
155
137
M35
33.0
155
158
KE3
36.0
155
142
STN41
36.7
155
130
STN43
39.5
155
108
STN45
41.5
155
103
(3) the conversion of cell CaCO3 into CaCO3 production involves numerous assumptions and room should be made to present the resulting growth rates from these estimates, and comparison of these with in situ estimates of growth rates and other more direct measurements of CaCO3 production (e.g., Daniels et al., 2018);
[Response]: We acknowledge that the conversion of cell CaCO3 into CaCO3 production involves numerous assumptions. This conversion is based on the standing stock and turnover time, which follows a study from the eastern Pacific (Ziveri et al., 2023). The range of turnover times used in our study is derived from both laboratory and field estimates, as well as simulations from a generalized coccolithophore model for the equatorial to North Pacific Ocean (Krumhardt et al., 2017).
Despite these assumptions, our approach allows for a reasonable assessment of CaCO3 production patterns across the study region. The estimated coccolithophore CaCO3 production rates, ranging from 0.8 to 2.1 mmol m−2 d−1 during the sampling period, align with globally reported in situ calcification rates and are consistent with observations from the North Atlantic subtropical region (Poulton et al., 2006; Daniels et al., 2018), lending confidence to our estimates. The consistency of our estimates with independent measurements suggest that our approach captures the general trends and magnitudes effectively.
(4) the three different statistical analysis of coccolithophore trends with environmental data (RDA, correlation, random forest) are presented and summarised in 2 paragraphs of the discussion, which barely allows any setting of the results in the context of coccolithophore ecology;
[Response]: We have removed the random forest analysis but retained the RDA results to highlight the influence of environmental variables on the total variation in coccolithophore community composition. Additionally, the Spearman correlation analysis has been used to illustrate the relationships between coccolithophore species-specific abundance and environmental factors (Fig. 9).
Revised Fig. 9. (a) Redundancy analysis (RDA) diagram illustrating the relationship between the coccolithophore community and environmental factors; (b) independent contribution of each environmental factor to coccolithophore community variation using hierarchical partitioning-based canonical analysis; (c) correlations between coccolithophore groups and environmental factors with color gradients denoting the significance of the Spearman’s correlation coefficient r. Asterisks represent the statistical significance (***p < 0.001, **p < 0.01, *p < 0.05). Chl a: chlorophyll a, DIC: dissolved inorganic carbon, TA: total alkalinity, Ωcalcite: saturation state with respect to calcite, PIC: particulate inorganic carbon, DIN: dissolved inorganic nitrogen (nitrate plus nitrite), NH4+: ammonium, SRP: soluble reactive phosphate, DSi: dissolved silicate, HOL: holo-coccolithophores and LPZ: lower euphotic zone species Florisphaera profunda and Algirosphaera robusta.
In response to the reviewer’s suggestions, we have expanded the discussion to better integrate the statistical analyses with coccolithophore ecological dynamics:
1. In the RDA analysis section: “In the tropical and subtropical Atlantic Ocean, coccolithophore communities exhibited greater variability vertically within the water column than horizontally, at spatial scales of hundreds to thousands of kilometers (Poulton et al., 2017). Distinct species distributions were identified based on the depth zones (upper euphotic, lower euphotic, and subeuphotic zones), which reflect the lifestyle of the species (Poulton et al., 2017; Balch, 2018). In the NPSG region, our results also reveal a distinct vertical distribution pattern (Fig. 4), which may be driven by factors such as light availability, temperature, and nutrient levels. These environmental variables likely contribute to the physiological diversity of coccolithophores. Between the two regions, there is a transition in dominance shifting from U. tenuis and E. huxleyi to Syracosphaera spp. and E. huxleyi (Fig. 5). This is consistent with the prior observations of Balch et al. (2019).”
2. In the Spearman’s correlation analysis section: “In the Atlantic Ocean, E. huxleyi has been observed to exhibit an increasing relative abundance with increasing latitude (Balch et al., 2019), a pattern consistent with previous studies (Holligan et al., 2010; Poulton et al., 2017). Unlike many other species, E. huxleyi has a widespread distribution, which is attributed to its ability to adapt to diverse environments through both phenotypic plasticity and genetic selection (Lohbeck et al., 2012; Rickaby et al., 2016b; Taylor et al., 2017). Although E. huxleyi is the most abundant coccolithophore species, our results indicate that less abundant species, such as C. leptoporus and O. fragilis, contribute significantly to coccolithophore calcite concentrations (Fig. 5). Their calcification is species-specific, predominantly driven by inherent biological traits, including cell shapes, coccolith types, and architectural variations, which are conservative features of coccolithophore biology (Rickaby et al., 2016a). However, their weak correlation with environmental factors may be attributed to their low abundance. Overall, our study highlights the significant influence of depths and latitude on coccolithophore community composition, emphasizing the complex interplay between biotic and abiotic factors.”
(5) the modelling approach to examine whether metabolic respiration drives CaCO3 dissolution in sinking particles has numerous inherent assumptions and completely ignores the potential role of zooplankton ingestion and digestion.
This last example includes some of the strongest examples of limited discussion, where some of the literature cited makes much more nuanced (or even opposite) conclusions about the relative roles of micro-environment and zooplankton led dissolution. This is an active research field and so the authors must fully discuss the different mechanisms proposed, especially if they are going to conclude that ‘our results indicate that shallow-water CaCO3 dissolution indeed occurs in the western North Pacific Ocean mainly as a result of metabolic acidification in the particulate microenvironment’ (Lns 416-417). Are the authors confident that their model results could not also be interpreted as dissolution in zooplankton guts (i.e. another microenvironment) and that their approach accurately compares both proposed mechanisms of dissolution? This section of the discussion also brings in several totally new concepts (Lns 411-414: Alk*, TA*, CFC age-based RTA, ALK*-transit time distribution, 14C-age based RTA values) to the paper with no background to their meaning, interpretation or limitations which is completely confusing at this (late) stage of the article.
[Response]: Thank you for these important comments. We acknowledge that this section of the model calculations is based on several assumptions and does not explicitly account for dissolution occurring in zooplankton guts. Our primary objective in this section was to compare the effect of metabolic activity (Ω influenced by in situ metabolism) and ambient Ω on shallow CaCO3 dissolution.
This content was based on the findings of Subhas et al. (2022) in the eastern Pacific, which yielded similar results in the western Pacific Ocean. However, considering the limitations of the model and the general comment that the article contains too much content, we have decided to remove the discussion in Section 4.4 as suggested. Additionally, calculations related to the water column tracer Alk*, which were originally included in the supplementary material, have also been removed.
There is considerable merit to the work done by Han et al., however a single paper does not do justice to the data collected or its interpretation, or the serious limitations and assumptions included in the methods employed. Given the missing methods on the environmental data and the brevity with which the results are discussed, it is difficult to fairly assess the work presented.
[Response]: Thank you for your thoughtful comments. We have added a detailed description of the methods for environmental data to improve clarity. The text has been modified in multiple sections to address the specific concerns raised. These revisions include significant rewriting of parts of the discussion, with expanded discussions on methodological uncertainties and the influence of environmental factors, as well as the removal of the discussion on shallow CaCO3 dissolution to ensure a stronger and more focused narrative.
Specific comments
Ln 1 (Title), Coccolithophores are only pelagic (not benthic) so suggest removing pelagic from the title. Also see general comments on content of the paper and consider what has been directly measured (cell counts, PIC) and what has only been estimated (production, dissolution).
[Response]: “Pelagic” has been removed as suggested. The new title is “Coccolithophore abundance and production and their impacts on particulate inorganic carbon cycling in the western North Pacific”.
We have refined the scope of our manuscript to focus primarily on the directly measured parameters, including coccolithophore abundance and PIC concentration, along with the estimation of CaCO3 production. To enhance clarity and maintain a focused narrative, the discussion on dissolution has been removed.
Ln 15, When describing a species as dominant, especially in light of the various metrics used in the paper, does this refer to numerical dominance?
[Response]: Here, “dominant” specifically refers to numerical abundance based on cell counts. This has been clarified in the revised text.
Ln 17, Is E. huxleyi the most important producer or contributor to the PIC standing stocks? High standing stocks along the sample transect does not necessary equate to CaCO3 production rates as growth rates between species vary and it is not clear if this statement includes detached coccoliths or not.
[Response]: We agree with the reviewer’s point and have revised the statement to focus on the overall contribution of coccolithophores. The revised sentence has been updated to:
“Calcite from coccolithophores accounted for an average of 76 ± 27% of the CaCO3 standing stock in Niskin bottle samples, with a higher contribution observed in the subtropical gyre region (91 ± 30%) compared to the Kuroshio-Oyashio transition region (65 ± 24%).”
Ln 18-19, It is strange to present the annual integrals in the abstract rather than the daily rates estimated to be associated with the observations collected. There are a lot of limitations and caveats to go from PIC concentration to growth rate, let alone to scale these to annual rates.
[Response]: Per your suggestion, we have revised the text in the abstract to present the daily rate associated with the observations collected. The revised sentence as follows:
“During the sampling period, coccolithophore CaCO3 production ranged from 0.8 to 2.1 mmol m−2 d−1, averaging 1.5 ± 0.7 mmol m−2 d−1 in the subtropical gyre and 1.2 ± 0.4 mmol m−2 d−1 in the Kuroshio-Oyashio transition region.”
Ln 19-20, What does the line ‘inorganic carbon metabolism driven by coccolithophores is relatively strong in oligotrophic ocean waters’ mean? Its meaning is vague and relatively strong (relative to where?) is not a quantitative term.
[Response]: We have removed this sentence from the revised text.
Ln 27, Surely CaCO3 production and dissolution are the two processes associated with CaCO3 cycling; the phrasing here implies that there are other processes involved. Also, it is not the ‘so-called’ carbonate pump, this is what it is called (Ln 28).
[Response]: We have revised the sentence to “Calcium carbonate (CaCO3) production and dissolution comprise CaCO3 cycling in the ocean, and are a key component of the global oceanic carbon cycle (Broecker and Peng, 1982) through the carbonate pump (Volk and Hoffert, 1985).”
Ln 33, This line does not follow (‘this acidification feedback mechanism’) the previous line or make sense. This might also be a good point to introduce carbonate chemistry and would help the reader.
[Response]: Following your suggestions, we have rephrased the relevant sentences as:
“Over the last decade, ocean acidification (OA), a global reduction in seawater pH caused by the uptake of anthropogenic CO2, has emerged as a significant feedback mechanism, making it harder for calcifying organisms to produce their skeletons, and thus adversely affects marine ecosystems (Feely et al., 2004; Ma et al., 2023a).”
Ln 40, Contrast this line (‘a major fraction’) with the values given in the preceding lines. Please give a value.
[Response]: We have added the value of 24–80 % to clarify this point in the revised manuscript.
Ln 41, What is a ‘data assessment’? Surely the Ziveri et al. (2023) paper is based on observations?
[Response]: We have revised the text to replace “data assessment” with “Field observations”.
Ln 43, This line (about large uncertainties) should link to the preceding line as there are large uncertainties in the composition of CaCO3 production between the different pelagic groups mentioned in line 42.
[Response]: We have revised the sentence by adding “as well as the contributions of different pelagic groups, which are still unclear and vary across regions.”
Ln 45, Daniels et al. (2018) is not listed in the references. Also, why are the values on Ln 46 in mg m-2 d-1 rather than mol (as in the abstract)? It should also be made very clear that the values given throughout the paper are in CaCO3 (i.e. mol/g = 100). Are the other values in the paper (PIC, CaCO3 production) given in CaCO3 or C?
[Response]: We have revised the value of <0.1 to 6 mmol m−2 d−1 with reference to Daniels et al. (2018). Also, we have now standardized the units throughout the manuscript. Specifically, standing stocks are expressed in mmol m−2, daily production rates in mmol m−2 d−1, and seasonally corrected annual production rates in mol m−2 yr−1.
Lns 48-49, Unnecessary repetition (‘along with the current scarcity of studies’).
[Response]: We have removed the sentence to eliminate unnecessary repetition.
Ln 50, This is a bold statement (‘CaCO3 dissolution is generally assumed to mainly occur below the saturation horizon’), especially based on the multiple references included in the article and that shallow dissolution has been recognised since the 1990s (e.g., Milliman e al., 1999 Deep-Sea Research) – this statement should have a reference or be modified.
Ln 57-58, See new paper by Oehlert et al., 2024 (GBC, doi: 10.1029/2024GB008176) arguing that high-Mg fish calcites have a very low PIC:POC and the POC associated with fish fecal pellets provides considerable protection as they rapidly sink.
Ln 59-60, Please expand on this issue in light of: Mayers et al. (2020, doi: 10.3389/fmars.2020.569896) and Dean et al. (2024, doi: 10.1126/sciadv.adr5453) which imply that (micro)zooplankton grazing can be an important loss process for coccolithophore CaCO3.
[Response]: Thank you for your valuable comments. We have removed this paragraph due to the removal of Section 4.4, as per your suggestion.
Ln 62-65, Please consider shortening and simplifying this sentence.
[Response]: We have revised the sentence into two shorter statements, the revised text is as follows: “In the eastern North Pacific Ocean, CaCO3 production, export, and dissolution have been studied along a transect from Hawaii to Alaska (Dong et al., 2019; Naviaux et al., 2019; Subhas et al., 2022; Ziveri et al., 2023). Ziveri et al. (2023) found that depth-integrated CaCO3 production in the nutrient-rich subpolar gyre is twice as high as that in the nutrient-poor subtropical gyre.”
Ln 65-66, Do these differences highlight deep CaCO3 production, or that the CaCO3 production is happening over a deeper euphotic zone?
[Response]: These differences highlight the importance of CaCO3 production over a deeper euphotic zone and the limitations of satellite products. The revised sentences as:
“indicating the importance of coccolithophore CaCO3 production over a deeper euphotic zone and the limitations of satellite products as highlighted by Neukermans et al. (2023).”
Ln 66-68, This line needs the relevant citations.
[Response]: We have added the references to Subhas et al. (2022) and Ziveri et al. (2023) in the revised manuscript.
Ln 69, coccolithophore should be coccolithophores.
[Response]: Modified as suggested.
Lns 74-76, There appears to be 4 research questions here, with (3) split into whether there is shallow dissolution, and a fourth on whether this is driven by metabolic activity. Further, while research questions (1) and (2) are clearly addressed by the data presented in the article, (3) and (4) are based on the addition of modelling to the discussion (see later comments) and it is unclear if these are addressed in the depth that they deserve.
[Response]: Thank you for your comment. Based on your suggestions, as well as related comments in the “general section”, we have removed Section 4.4 from the manuscript. Additionally, we have revised and simplified the research questions, retaining only (1) and (2) that are directly addressed by the data presented in the article.
Ln 89, Figure 1 – The colour bar used means that there are two bands of yellow (one around 0.75 and one at the maximum value), which is confusing. Also, the precise dates for the composites are not included (are these 1-30th June)?
[Response]: We have modified Figure 1 by adjusting the color bar to improve visual clarity. Also, the precise dates were included.
Revised Fig. 1. (a) Map of the western North Pacific Ocean showing sampling stations (black filled circles) and major surface currents (solid black lines); (b–d) satellite-based temperature, chlorophyll a (Chl a) and particulate inorganic carbon (PIC) concentrations in surface water from 1st to 30th June 2022 (data from the Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua satellite; https://oceancolor.gsfc.nasa.gov/l3/).
Ln 99, Based on the use of ‘filters’ in the next line of the method (‘filters were oven-dried’) suggest adding membrane filters to the preceding line to avoid confusion – unless the SEM filters weren’t dried and stored in petri-slides?
[Response]: Modified to “Membrane filters” as suggested.
Ln 103, Does large and small fractions of PIC need a unique abbreviation, or could they just be referred to as small and large? There use (and non-use at times) in the article is confusing. Also, does PICtotal need an abbreviation, or could it just be referred to as total PIC?
[Response]: Thank you for your comment. The terms “small”, “large”, and “total PIC” are used consistently throughout the revised manuscript.
Ln 110, Do the authors mean the analytical precision was <10%? The use of ‘better than’ is confusing.
[Response]: Modified to “<10 %” as suggested.
Ln 112, Phrasing confusing – sounds like only some of the filters collected were mounted, do the authors mean a portion of the filters was mounted?
[Response]: We have clarified this by rephrasing the sentence as “Filters were cut and mounted with a carbon sticky tab on a stub and gold-coated prior to analysis using a Quanta 650 FEG field-emission scanning electron microscope (SEM).”
Ln 120-121, Have the authors seen the article by Sheward et al. (2024, doi: 10.1038/s41597-024-03544-1)? A comparison between the cell PIC values in these articles would be a valuable addition to the literature. As the scaling from cells to cell PIC is key to this article, some comments around potential sources of error and limitations (e.g., accurately assessing the number of coccoliths) should be included. Also, ‘all the’ is unnecessary in the second line.
[Response]: Please refer to our response in the “general comments” section.
(1) We have expanded the description of the morphometric-based calcite estimation method, and the calculation of coccolith PIC is now detailed in Supplementary Table 2.
(2) We have added the discussion of the potential errors and limitations associated with the morphometric-based calcite estimation method including the work of Sheward et al. (2024).
In addition, “All the” has been moved as suggested.
Ln 124, Do the authors mean shallower than 150 m or deeper (i.e. above) 150 m? Also, why 150 m? This is unlikely to be the euphotic depth across the entire transect.
[Response]: Based on your suggestion, we have revised the integration depth to the euphotic zone depth for each station, and thus changed “above 150 m” to “in the euphotic zone”.
Ln 125-126, Why are the turnover times and division rates given here different than from Ziveri et al. (2024)? What were the growth rates that resulted from these estimates? What are the potential sources of error and uncertainty with this method of estimating CaCO3 production?
[Response]: Thank you for your questions. The turnover times and division rates provided in our study are slightly adjusted compared to Ziveri et al. (2023), which reported a range of 0.6–10 days and 0.1–1.5 cell division day−1. In our analysis, we used a range of 0.7–10 days, as the lower bound reflects the division rate of 1.5 divisions day−1, where 1/1.5 = 0.66, rounded to 0.7 days.
Regarding potential sources of error and uncertainty, we have revised the text by adding:
“The coccolithophore turnover time was derived from both laboratory and field estimates, as well as simulations from a generalized coccolithophore model, which has also been applied to the eastern North Pacific (Krumhardt et al., 2017; Ziveri et al., 2023). We are aware that different coccolithophore species exhibit widely varying growth rates, and cell growth phase differs for smaller cells produce fewer coccoliths during the exponential growth phase (characterized by rapid division), whereas larger cells generate more coccoliths during the early stationary phase, when cell division slows down (Raven and Crawfurd, 2012; Krumhardt et al., 2017). We also acknowledge that estimating coccolithophore calcite and production rates using an average coccolith calcite value introduces uncertainties, as this approach does not fully account for the complexities of coccolith dynamics, including rapid cycling and reabsorption (Johns et al., 2023). Despite these possible errors and uncertainties, our estimations are consistent with direct production rate measurements of Daniels et al. (2018), suggesting that our data provide a reliable basis for assessing coccolithophore calcification dynamics.”
Ln 134, No methods are included for the environmental conditions. Much more details are needed for these parameters, such as detailed methods including internal standards, precision estimates, and CRMs. These are all included as standard with the environmental data and as presented as such there is little confidence in the quality of the environmental data as this cannot be assessed as part of the review. As these are key to the following sections of the manuscript and the calculations made, they must be presented in detail here.
[Response]: Method details were previously included in the supplementary material, and have now been incorporated into the main text. Please refer to our response in the general comment section for a detailed explanation.
Ln 142, Why is only the effect of microenvironment undersaturation considered? Would the same configuration describe dissolution driven by metabolic activity inside zooplankton guts? Surely to test the dominant driver of CaCO3 dissolution, all potential drivers need to be considered? On Ln 143, the assumption that aerobic metabolic activity consumes all ambient oxygen is a significant assumption – do the sub-surface waters go anoxic or are the authors suggesting that internal environments in sinking marine snow are anoxic? If the authors remove this assumption, can they still get these patterns of dissolution?
[Response]: This section describes the calculation method for calcium carbonate dissolution. Since the discussion on dissolution in Section 4.4 has been removed, this part has also been correspondingly deleted from the revised manuscript.
The one-dimensional model employed in the former version of our study followed the framework established by Subhas et al. (2022) and Dong et al. (2019). This model assumes that the interiors of marine snow aggregates exhibit lower pH and consequently lower Ω, compared to ambient seawater, due to the production of respiratory CO2 (Milliman et al., 1999). Despite the uncertainties introduced by the assumptions in this modeling approach, our results suggest that the respiration of organic carbon is responsible for a substantial portion of CaCO3 dissolution in the upper ocean.
Although zooplankton grazing was not explicitly modeled in our study, it may be captured implicitly in the Ωmet framework (Subhas et al., 2022). We acknowledge that microzooplankton grazing plays a role in shallow CaCO3 dissolution, as a recent finding suggested this mechanism could account for 50 to 100% of the observed CaCO3 dissolution in supersaturated surface waters (Dean et al., 2024). Therefore, it is important to constrain the relative contributions of different mechanisms to shallow CaCO3 dissolution.
Ln 166, Do the authors mean nutricline, as related to multiple nutrients, or the nitracline, as related to nitrate. As the authors describe this in terms of nitrate, this seems to be the nitracline. Following on from this (Ln 175), why was the depth where DIN reached 0.1 umol/L used rather than (as more commonly used) 1 umol/L? Was this something to do with the detection limits of the measurements, in that 0.1 umol/L is a common threshold for nitrate+nitrite detection and so this effectively describes the first depth where nitrate was detectable? Without the detailed methods on the environmental parameters, it is difficult to assess this criterion. Finally, why is this depth not plotted on Figure 2?
[Response]: The corresponding methodological description has been added. Please refer to the earlier response for details. We acknowledge that using nitracline rather than nutricline is more appropriate in this context. Regarding the using of 0.1 µmol L⁻1 as the DIN threshold, we followed the method of Ma et al. (2023b), which defines the top of the nitracline as the depth where the DIN concentration reached 0.1 µmol L⁻1 (Dore and Karl, 1996; Winn et al., 1995). However, 0.1 µmol L⁻1 is not the detection limit, we also measured nanomolar-level DIN concentrations with a detection limit of 5.2 nmol L⁻1. Nevertheless, we have removed the content related to the nutricline in the revised manuscript, as it is not directly relevant to the main focus of this work.
Ln 171, What is the justification for using 0.03 mg m-3 to define the transition in density at the base of the mixed layer? The authors should give a reference as there are multiple criteria and methods used to define the mixed layer. Also, did the mixed layer depth vary by 11-25 m around a value, or do they mean that the mixed layer varied from 11 to 25 m in depth? How does this compare with their assumption of a 150 m euphotic zone depth?
[Response]: The mixed layer, defined following Ma et al. (2023b) and ranged in depth from 11 to 25 m, which is shallower than the euphotic zone depth. We have removed the content of the mixed layer depth. While this information is relevant for understanding the physical dynamics of the water column, we realized that it is not directly critical to the main focus of our study.
Ln 181, Figure 2 – The authors should be wary of using ODV with sparse data as it tends to expand data beyond the sample depths with a horizontal bias (kms) rather than vertical (ms) one and creates (sometimes fictional) patterns. These can be seen clearly in this Figure; for example, the DCM (e) is at ~70 m at 35oN, but there are no samples to confirm that, PIC is stretched around 40oN both N and S at a depth of around 30 m but there are no sample points to support this pattern. Similar comments can be made with panels (g) and (f). As these are key parameters for the paper, the authors should consider different ways of plotting the data that more accurately represent the patterns and spatial limitations of the data.
[Response]: Based on your suggestion, we have adjusted the rendering range and increased the visibility of the sampling points to better represent the spatial coverage of the data.
Revised Fig. 2. Vertical depth distributions of (a) temperature, (b) salinity and concentrations of (c) soluble reactive phosphate (SRP), (d) dissolved inorganic nitrogen (DIN, nitrate plus nitrite), (e) Chlorophyll a (Chl a), (f) particulate inorganic carbon (PIC), (g) coccosphere cell and (h) detached coccoliths in the upper 300 m of the water column in the study area.
Ln 187, How much of the apparent pattern of low PIC in the surface and increasing with depth is driven by the contouring in Figure 2? In Figure 3 why are no error bars included to give an idea of the relative patterns? Also, in terms of Figure 3, why are the three sets of measurements at different depths - they do not line up? How does this impact the interpretation of the data?
[Response]: The apparent pattern of low PIC in the surface and its increase with depth is indeed a reflection of the observed data, not an artifact of the contouring process in Figure 2. Figure 2 has been revised to clarify which features are supported by the data. Figure 3 also includes plots of the PIC concentration data as a function of depth without the ODV interpolation, and we have revised it by including error bars.
In some cases, there was a slight mismatch between the pump depths and the depths of the Niskin bottles, as these were separate deployments. Despite this discrepancy, we believe it does not affect the results, as the data obtained from the two methods are comparable.
Revised Fig. 3. Vertical depth distributions of particulate inorganic carbon (PIC) concentrations derived from sampling using both Niskin bottles and in situ pumps (small size fraction of 1–51 μm and large size fraction of > 51 μm) in the upper 350 m of the water column at sampling stations in the study area.
Ln 192, In the methods section (Ln 118) the detection limits for coccolithophore cell counts from SEM is given as 1.87 cells mL-1, but line 192 reports cell concentrations of 0.97 cells mL-1 (=970 L-1)? Please explain this discrepancy.
[Response]: Thank you for pointing out this issue. While the detection limit for coccolithophore cell counts from SEM is 1.87 cells mL⁻¹, there were four samples with cell concentrations below this threshold, due to the low coccolithophore abundance in these specific samples. We chose to include these data for completeness and to maintain consistency in the dataset, and we have added a note of “The coccolithophore abundance in four samples was extremely low, falling below the detection limit. While this may lead to potential inaccuracies, these values are still meaningful as they indicate an exceptionally low coccolithophore presence at these depths.” in the revised manuscript. Importantly, this does not impact the conclusions of the study.
Ln 196, Here the authors talk about averages, but the preceding lines gave specific concentrations, and it is not clear what this value for coccoliths is for – all depths, all stations? As the difference between subtropical and subpolar waters is a strong theme of the paper wouldn’t it make sense to compare the averages for these?
[Response]: The average value reported here represents the detached coccolith concentration across all stations, which differs from the coccosphere cell concentration in preceding lines.
We did not conduct a comparison between the two regions because no significant variation of detached coccolith was observed.
Ln 211, What does predominantly mean when used here – do these refer to coccosphere abundances?
[Response]: Yes, “predominantly” refers to coccosphere abundances. We have clarified this point in the revised manuscript by “each comprising > 1 % of total coccosphere abundance”.
Ln 213, Do all species listed in lines 211 to 213 compromise >1% of total coccosphere abundance or just F profunda?
[Response]: All the species listed comprise more than 1% of the total coccosphere abundance. We have clarified this by using “each comprising” in the revised manuscript.
Ln 216, Did E huxleyi contribute the largest fraction in every sample?
[Response]: E. huxleyi contributed the largest fraction in most samples, except for the samples from M30 and M32 in the subtropical region, where U. tenuis was the dominant contributor.
Ln 219, What is the lower euphotic zone (LPZ) and how are coccolithophore species assigned to this depth? Is there a missing reference here?
[Response]: The lower euphotic zone (LPZ) refers to the water column receiving 10–1% of surface irradiance. Coccolithophore species assigned to this depth include Florisphaera profunda and Algirosphaera robusta, which are adapted to thrive under low-light conditions (Jin et al., 2016; Poulton et al., 2017). We have clarified this point in the revised manuscript.
Ln 225, Figure 4 – Beyond E huxleyi there is very little detail visible in this plot, could the authors present this as percentage contributions rather than cell abundances? Do the authors want to emphasise abundance or species diversity in this figure?
[Response]: Based on your suggestion, we have revised Figure 4 to present the data as percentage contributions instead of cell abundances.
Revised Fig. 4. Relative abundance of different coccolithophore groups in the upper 300 m of the water column. Lower euphotic zone (LPZ) species include Florisphaera profunda and Algirosphaera robusta; HOL indicates holo-coccolithophores.
Ln 229, Is the coccolithophore CaCO3 really 0.00 umol L-1 or <0.01 umol L-1?
[Response]: We have revised the value to “<0.01 μmol L−1” in the revised manuscript.
Ln 234, Why are exact numbers or ‘ca.’ given elsewhere in the article but “~” is used here to indicate approximately?
[Response]: We have removed “~” in the revised manuscript.
Ln 238, Figure 5 – What does this show? Are these averages for the all stations, all depths? How does this add to the theme of the paper in terms of latitudinal or vertical differences? Being Pie Charts this automatically presents percentage contributions, so if these are averages then there is no option to show error bars and compare the different components. Is this the best way to present the data or compare sampling depths/regions?
[Response]: We have revised this figure to better illustrate the differences in the contributions of various coccolithophore groups to coccosphere cell abundance, detached coccolith abundance, and coccolithophore calcite concentration between the NPSG region and the Kuroshio-Oyashio transition region. Percentage values have also been added.
As the figure represents an analysis of combined samples from all stations within each region, it presents aggregated data and does not include error bars.
Revised Fig. 5. Contribution of different coccolithophore groups to coccosphere cell abundance, detached coccolith abundance, and coccolithophore calcite concentration in the upper 300 m of the water column: (a–c) in the North Pacific Subtropical Gyre (NPSG: M30, M32 and M35) and (d–f) in the Kuroshio-Oyashio transition region (KE3, STN41, STN43 and STN45). Lower euphotic zone (LPZ) species include Florisphaera profunda and Algirosphaera robusta.
Ln 234, Does this mean the measurements were integrated from the surface depth to 150 m? What was the argument for 150 m (in view of changes in the euphotic zone depth)? How shallow were the shallow depths and were they consistent? Would it not be more consistent to assume that the unsampled surface depth was the same as the shallowest sampled depth?
[Response]: The measurements were originally integrated from 10 m to 150 m depth. We have now revised the integration depth to the euphotic zone depth for each station.
Regarding the shallowest sampling depth, the Niskin bottle samples were collected at 10 m, and this was consistent across all stations. For the in situ pump samples, data at 10 m were used when available. For stations lacking 10 m data, the TREND interpolation method was applied to fill this gap.
Lns 244 onwards, Are these concentrations in mg CaCO3 m-2 or mg C m-2? Are they averages for the different areas, and if so, what are the standard deviations?
[Response]: The standing stock initially reported was mg CaCO3 m−2 and has been changed to mmol m−2. We have also added the corresponding standard deviations in the revised manuscript.
Ln 243, Figure 6 – This is a very difficult figure to understand. (a) Why are area averages given now whereas elsewhere in the paper the latitudinal pattern is emphasised? Where are the error bars for the averages? Is the data normally distributed? Why is the coccolithophore contributions surrounded by orange? Are the average bottle and sum of small and large (note no abbreviation of SSF and LSF are used) significant the same when compared? (b) The data here is obviously not normally distributed and generally the estimates of CaCO3 production tend towards lower values – however (!) the blue diamonds, which are not defined in the legend and so are we to assume they are averages, are offset higher than the data is distributed. This looks to be an example of where a geometric mean should be used, and the values should be lower than the blue diamonds – indicating that the authors are overestimating CaCO3 production at the different stations. Please explain.
[Response]: Thank you for your detailed comments on Figure 6. We have made the following changes to improve clarity and address your concerns:
The figure has been revised to include CaCO3 standing stock data for the euphotic zone at each station. Error bars have been added to the regional averages. For consistency, the terms for large and small PIC are unified in the revised manuscript.
Regarding CaCO3 production, we apologize for the offset observed in the previous version of the figure. This issue arose due to the plotting function in MATLAB. We have now reprocessed the data using the R package vioplot to better represent the distribution. The blue diamonds indicate the median values, which correspond to the peak of the probability density in the violin plot.
Revised Fig. 6. Calcium carbonate (CaCO3) standing stock in the euphotic zone estimated from Niskin bottle particulate inorganic carbon (PIC), total calcite (Cocco) and size-fractionated (large and small fractions indicate > 51 and 1–51 μm, respectively) PIC concentrations (a) at each sampling station and (b) in the North Pacific Subtropical Gyre (NPSG) and Kuroshio-Oyashio transition regions; (c) CaCO3 production by coccolithophores in the euphotic zone at indicated sampling stations in June-July 2022; (d) annual CaCO3 production corrected for seasonal bias using satellite-derived PIC concentrations. The blue diamond marks the median value, while the shaded area displays the probability density of the estimates. The grey lines denote the quartiles (the 25th and 75th percentiles).
Ln 258, This is the first mention of in situ pump data since the methods and so is slightly confusing in terms of SSF and LSF (small and large PIC particles). Also, are the values here mg CaCO3 m-2?
[Response]: We had previously mentioned in situ pump data in the final paragraph of Section 3.2. The values initially reported here are in mg CaCO3 m−2 and have been changed to mmol m−2 in the revised manuscript.
Lns 262-263, Not clear at all as to how the CaCO3 production rates presented here follow from the statement about turnover times. Would it not make sense to present the growth rates that derive from the estimates of CaCO3 production and compare these with measured growth rates in the open ocean? Are the growth rates estimated similar between the two different regions and thus the differences (or similarities) driven purely by the standing stocks of PIC? What would clarify this would be to present in Figure 6 the integrated PIC for all the stations, the growth rates estimated for each station and the CaCO3 production – this way, the reader can follow how the three interact.
[Response]: The detailed calculation method is described in Section 2.3 “Estimation of CaCO3 production rate”. The turnover time used here was derived from growth rates, based on the data from Krumhardt et al. (2017), which incorporate both measured values and model estimates, rather than being calculated from CaCO3 production. In addition, a similar calculation has already been applied in the eastern Pacific, further supporting the validity of our approach (Ziveri et al., 2023). We acknowledge that a unified turnover time was used, which means that the estimates of CaCO3 production are largely driven by the standing stocks of PIC. To provide clarity, we have revised Figure 6 to include the integrated PIC for all the stations.
Ln 267, On lines 265 to 266 the link between high CaCO3 production and high cell numbers is established, whereas the comparative information is not given in Ln 267; does the lowest CaCO3 production correspond to the lowest cell counts?
[Response]: The lowest CaCO3 production does not correspond to the lowest cell counts. This discrepancy could be attributed to differences in species compositions, as certain coccolithophore species have higher calcification rates per cell. As we changed the integration depth from 150 meters to the euphotic zone depth, the results will change accordingly. We have clarified this point in the revised manuscript by “Coccolithophore CaCO3 production was maximal at station M30 and the lowest coccolithophore CaCO3 production was observed at station M35.”
Lns 271-278, All this material appears to be introductory material and is a repeat of what has been said in the introduction.
[Response]: We have removed this section in the revised manuscript.
Ln 282, The authors should consider citing Poulton et al. (2017, doi: 10.1016/j.pocean.2017.01.003) alongside Balch et al. (2019) in terms of defining depth flora in the subtropics.
[Response]: We have added a citation of Poulton et al. (2017).
Lns 282-285, Statements around coccolithophore nutrient stress and cell quotas are best backed up by physiological references, not modelling references.
[Response]: Accordingly, we have revised the manuscript by incorporating relevant physiological studies to better support our discussion.
The revised section as: “Coccolithophores are nutrient stress tolerant and have low iron cell quotas, and are thus generally abundant in the open ocean (Gregg and Casey, 2007; Brun et al., 2015). Studies have shown that coccolithophores, particularly E. huxleyi, can thrive under low inorganic iron conditions more effectively than other phytoplankton such as diatoms, due to their inherently lower cellular iron demands (Hartnett et al., 2012; Balch, 2018). However, when nutrients and light are plentiful, the heavy coccoliths of this group of phytoplankters pose a selective disadvantage over diatoms and chlorophytes (Gregg and Casey, 2007). The dominance of coccolithophores in the Great Calcite Belt (GCB) is primarily driven by their adaptation to low iron levels and the dual limitation of diatoms by both silicate and iron, which provides favorable conditions for coccolithophore growth (Balch et al., 2016).”
Ln 288, O’brien et al. should have a capital; O’Brien et al., 2016.
[Response]: We have corrected it in the revised manuscript.
Lns 292-296, It is impossible to assess the RDA without details of the methods for the environmental data and some statements around whether the authors checked for autocorrelations between the different variables. Also, what is the justification for putting in some variables, for example latitude or depth? Latitude should correlate with temperature and is depth supposed to represent a pressure effect or light availability. It would be good to see some mechanistic physiological exploration of how the variables included in the RDA impact on coccolithophore growth (as this underpins the CaCO3 production estimated). Are all the variables included necessary? This also goes for the Spearman comparison. In general, there is so little discussion of this in the discussion that this analysis comes across as very superficial (13 lines) despite including three different statistical tests of the data that are not found in the results.
[Response]: The methodology for the environmental data (e.g., Chl a, nutrients and carbonate chemistry), has now been incorporated into the main text. We acknowledge that latitude mainly correlates with temperature, and depth is also closely related to temperature gradients. For the Spearman correlation analysis, we opted to include all variables to provide a comprehensive overview of potential relationships among environmental parameters and coccolithophore species abundance.
We have considered the potential autocorrelation between the different environmental variables and conducted a screening process to minimize redundancy. We have updated the methods section to reflect these considerations with the following statement:
“The redundancy analysis (RDA) is a widely used multivariate analytical method to identify relationships among individual variables in different categories. Prior to the RDA, statistical differences in environmental variables were evaluated using an analysis of variance (one-way ANOVA), while collinearity between environmental variables was accounted for by calculating variance inflation factors (VIF). Forward selection of variables was subsequently carried out until all VIF scores were <10, in order to only include variables that are not significantly correlated. These criteria reduced the number of environmental variables used in the RDA. Monte Carlo permutation tests, based on 1000 randomizations, were performed to identify the most significant and independent effects on variation in the composition of the coccolithophore community. The overall significance of the explanatory variables after forward selection was evaluated through ANOVA (α<0.05) and coefficient of determination (r2) and adjusted r2 were calculated to assess the power of a selected RDA model using the vegan package (Oksanen, 2010).”
Please refer to our response in the “general comments” section.
Lns 325-327, The authors need to expand on their reasoning here – how do relationships between coccolith and coccosphere concentrations indicate that the detached coccoliths came from living cells and where not (e.g.) advected into the area, from viral lysis of cells or disintegration of the coccospheres after grazing or from faecal pellets or programmed cell death?
[Response]: Thank you for the suggestion. We have accordingly revised the relevant sentences: “It is noteworthy that detached coccolith concentrations of E. huxleyi, U. tenuis and Syracosphaera spp. showed a significant positive relationship with their coccosphere cell concentrations (Fig. 7b–d), indicating that those detached particles were likely shed by cells as part of the dynamic calcification process, where coccoliths are continuously produced and released (Johns et al., 2023). However, other potential sources, such as advection and processes, cell disintegration from viral lysis and grazing, fecal pellets, or the dissolution associated with microbial respiration could also contribute to the observed detached coccolith concentrations (Vincent et al., 2023; Subhas et al., 2022; Dean et al., 2024). Coccolith production and shedding are dynamic processes, with fast-growing species like E. huxleyi producing and shedding coccoliths rapidly during exponential growth phases, whereas other species exhibit different patterns, which are influenced by their distinct physiological and ecological characteristics (Johns et al., 2023).”
Ln 329, Figure 8 – These plots miss the sample number for the different species and it is surprising that despite the variability in presented sample number and data distribution, the p values for all the plots are p<0.01. Are these plots all forced through zero?
[Response]: We confirm that the plots in the original version were forced through the origin, whereas the revised plots are not.
We have revised the figure per your suggestions, and the p values for all the plots are <0.01. For E. huxleyi, although the result is statistically significant (p <0.01), the correlation remains weak, as indicated by the low r2 value.
As a result of the structure adjustments, the original Figure 8 is now referred to as Figure 7 in the revised manuscript.
Revised Fig. 7. Relationship of (a) coccolithophore calcite (coccospheres and the detached coccoliths) vs particulate inorganic carbon (PIC) concentrations and (b–d) detached coccolith vs coccosphere cell concentrations for (b) Emiliania huxleyi, (c) Umbellosphaera tenuis and (d) Syracosphaera spp. in the upper 300 m water column at the study site. Equations describing the fitted straight lines are also shown.
Ln 333, This is the first mention of aggregates in the text. The authors need to expand on this and explain how they were measured/identified/classified etc.
[Response]: In the scanning electron microscope (SEM) analyses, “aggregation groups” refer to clusters formed by multiple coccolithophores grouped together. In this study, we only quantified their abundance but excluded them from coccolithophore calcite calculations, as it is challenging to accurately determine the number of individual coccoliths within these aggregates.
We have added details in the “methods” section as: “Aggregates formed by clusters of multiple coccolithophores were quantified in terms of abundance but were excluded from the coccolithophore calcite calculations, mainly due to the difficulty in accurately determining the number of individual coccoliths within the aggregates.”
Ln 336, How does the statement of the role of large species link to the results presented in the article? Do the authors see these species, and do they make large contributions? Same comment on lns 337-339.
[Response]: In the results section, we stated that the less abundant (<3 %) species Calcidiscus leptoporus and Oolithotus fragilis accounted for 21 % and 12 % of the coccolithophore calcite concentration in the NPSG region and the Kuroshio-Oyashio transition region, respectively. This demonstrates that while these species are numerically less abundant, they contribute significantly to the total coccolithophore calcite concentration due to their larger calcite production per cell. This finding aligns with the results of Rigual Hernández et al. (2020) and Daniels et al. (2016), highlighting the relatively rare but heavily calcified species are important contributors to both upper-ocean calcite production and deep-sea calcite fluxes. We have further clarified this point in the revised manuscript.
Ln 341, Is not the point being made before that large, rare species can play important roles on CaCO3 production and export? Based on the preceding references (e.g., Daniels et al., 2016) and comments this seems to better follow.
[Response]: Please refer to the response to your previous comment. Yes, we have rewritten this section in the revised manuscript as “larger and less abundant coccolithophore species can play an important role in CaCO3 production and export.”
Ln 347-348, Why do the authors consider that ‘CaCO3 is largely produced in the lower layer of the euphotic zone’ when calcification is a light-dependent process? Is this what is seen in other studies of CaCO3 production (e.g., Daniels et al., 2018). References are needed here, and this should be expanded as it is a (potentially) important point. Or, do the authors mean that CaCO3 production occurs over a significant portion of the euphotic zone and not just the surface? As the authors did no measure CaCO3 production, how does this relate to their results?
[Response]: We would like to clarify that our statement refers to coccolithophore production occurring across a significant portion of the euphotic zone, rather than being limited to the surface. This is illustrated by Figure 2, where both PIC and coccosphere concentrations exhibit maxima near the layer of deep chlorophyll maximum, indicating substantial CaCO3 production in the lower euphotic zone. Although we did not directly measure CaCO3 production, these patterns provide evidence of production dynamics. In the revised manuscript, we have rewritten the sentence as “In these oligotrophic and low productivity oceans, a subsurface PIC maximum can develop within the euphotic zone, and the highly variable subsurface PIC concentrations are poorly reflected by satellites, potentially limiting the ability to fully capture coccolithophore contributions.”
Ln 353, Is ‘flux’ the correct term in this line? Do the authors mean that subsurface coccolithophore CaCO3 contributed significantly to the total water column PIC? Where does the flux relate to this?
[Response]: We agree with your suggestion and have replaced the term “flux” with “concentration”.
Ln 354, Is this what the authors observed in their data – i.e. large and PIC heavy species in the subtropical gyre?
[Response]: Yes, this observation is supported by Figure 5. These species are present not only in the NPSG region but also in the Kuroshio-Oyashio transition region. The sentence has been revised to: “Coccolithophore groups were diverse in the subtropical gyre, including some rare but larger and more heavily calcified species that contribute significantly to CaCO3 production.”
Lns 356-358, The final statement is confusing – why would low surface PIC values imply that coccolithophore CaCO3 production over the whole water column is not important?
[Response]: We agree that the original statement could be misleading and have revised it as: “Given that low surface PIC regions (< 0.1 mmol m–3) occupy about 87 % of the global ocean surface (Ziveri et al., 2023), our data highlight the significant contribution of these regions to global CaCO3 production.”
Ln 360, Are the values in this line averages? What are the standard deviations and are these values significantly different?
[Response]: The values provided are averages and the corresponding standard deviations have been added in the revised manuscript. While statistical tests indicate insignificant differences between these values, the observed trends suggest that the contribution of large PIC is higher in the Kuroshio-Oyashio transition region than in the NPSG region.
Ln 361, Is the LSF PIC mentioned here from this study or Ziveri et al. (2023)?
[Response]: Yes, it is. Ziveri et al. (2023) had been cited.
Ln 363-366, These lines need to be better related to the results presented, here they just appear as statements without the context of the present study.
[Response]: We have added the relevant sentence “These findings support our results and suggest that the relatively higher contribution of large PIC in the northern regions of the western North Pacific is likely attributed to foraminifera.”
Lns 368-371, This is a large leap here from discussions of pelagic calcifiers and different groups, to how ecosystem structure impacts the relative importance of different calcifiers – for example there are no data or statements in terms of other phytoplankton groups and the nutrients they are dependent on, the availability of prey for heterotrophic calcifiers, etc. This statement needs far more background and justification. No abundances of non-calcareous phytoplankton are given or attempts to estimate the amount of the phytoplankton community that coccolithophores represent, or how these changes between sites.
[Response]: While we do not have direct data on non-calcareous phytoplankton abundances, we have added references of previous studies observing latitudinal gradients in diatom biomass and planktonic foraminifera abundance in the North Pacific (Hirata et al., 2011; Sugie and Suzuki, 2017; Taylor et al., 2018). Furthermore, we have included supporting evidence from sediment trap data in the North Pacific, which indicate lower fluxes of planktonic foraminifera, organic matter, and biogenic opal in the subtropical region than in the transitional and subarctic regions (Eguchi et al., 2003). These additions help to better discuss the influence of ecosystem structure on the relative importance of different calcifiers across regions.
Ln 375, Figure 9 – It is not possible to see all the Pie Charts of the data from the present study so represents a poor figure trying to compare studies. Also, how do the authors know that the <51 um fraction is only coccolithophores and (e.g.) not shell fragments of foraminifera?
[Response]: Thank you for your comment. We have revised this figure by using euphotic zone-integrated data. We have retained the pie chart format as it facilitates a straightforward latitudinal comparison, and added data related to each pie for better visibility.
Regarding the <51 μm fraction, we contend that contributions from shell fragments of foraminifera are possible. However, our comparisons between bottle-sampled PIC, coccolithophore calcite, and size-fractionated PIC data suggest that the <51 μm fraction is primarily derived from coccolithophores.
As a result of the structure adjustments, the original Figure 9 is now referred to as Figure 8 in the revised manuscript.
Revised Fig. 8. Pie charts showing the composition of the total calcium carbonate (CaCO3) standing stock in the euphotic zone of the western (this study) and eastern North Pacific Ocean (data from the CDisK-IV cruise; Ziveri et al., 2023). Red represents the standing stock of large size fraction (> 51 μm) CaCO3 from this study, and planktonic foraminifera, pteropods and heteropods from the CDisK-IV cruise. Blue represents the standing stock of small size fraction (1–51 μm) CaCO3 from this study and coccolithophores from the CDisK-IV cruise.
Ln 381, As the title of the paper is around CaCO3 production it is surprising to see that only two paragraphs of the discussion cover this subject – it seems rather a light touch for a key parameter of the paper. Have the authors considered comparing their measurements with other sources of rate data (e.g., Daniels et al., 2018) or estimates of coccolithophore growth rates in the ocean?
[Response]: Thank you for your suggestion. We have added comparisons between our results and those of other studies, which read “Our results indicate that the coccolithophore CaCO3 production ranged from 0.8 to 2.1 mmol m−2 d−1 during the sampling period, align with globally reported in situ calcification rates and are consistent with observations from the North Atlantic subtropical region (Poulton et al., 2006; Daniels et al., 2018).”
Ln 383-384, Can the authors check the values given from Balch et al. (2007) and Hopkins and Balch (2018) as we cannot find these area specific rates in either publication, both deal with global PIC production using slightly different (but related) physiological-based models.
[Response]: Balch et al. (2007)’s value of 0.4 mol m⁻2 yr⁻1 was obtained from Ziveri et al. (2023), which has been removed in the revised manuscript. We have also removed the reference of Hopkins and Balch (2018) because this article only provides a global coccolithophore calcification rate of 1.42 ± 1.69 Pg C per year.
Lns 390-392, Does this statement relate to the data presented in this article? If so then it is a concern and considerably more should be said as to possible sources of these errors and inconsistencies (e.g., scaling from cell numbers to PIC concentrations).
[Response]: This statement refers to findings observed in the eastern Pacific, which are to some extent contrary to our data and results showing better consistency between estimated coccolithophore calcite concentrations and measured seawater PIC concentrations. We acknowledge that there are inherent uncertainties in the calculation of coccolithophore calcite concentration from cell numbers. Nevertheless, we would like to emphasize that our direct measurements of PIC concentrations in seawater helped to validate the estimated coccolithophore calcite concentrations.
Following the reviewer’s suggestions, the entire section of shallow CaCO3 dissolution has been removed in the revised manuscript. However, below we still responded to specific comments raised by the reviewer.
Ln 399, Do the authors consider 150 m to be the euphotic zone along the entire transect? This seems highly unlikely due to the changes in vertical distribution of the phytoplankton community (i.e. Chl-a). Some statements are needed in the article about what 150 m represents and what the authors consider in terms of the difference (or not) between the euphotic zone depth and 150 m.
[Response]: We have used the euphotic zone depth instead of a fixed depth of 150 m across the transect. Please refer to our response in the “general comments” section.
Ln 404-406, How did the authors do a one-way ANOVA on PIC distribution patterns? More needs to be said or shown in terms of what data has been compared and how the authors consider different water parcels or hydrographic regions. This seems a rather throw away comment that needs far more background; it would not be normally expected that an ANOVA on hydrographic data distributions is a valid statistical approach.
[Response]: We acknowledge that a one-way ANOVA is not good enough and have removed this part of discussion.
Ln 409, This is a significant assumption (that 100% of coccolithophore production is exported out of the euphotic zone) and needs far more discussion, including references and exploration of how if this was wrong it would impact on the article’s conclusions. Recognising that coccolithophores could be heavily grazed by microzooplankton (Mayers et al., 2019, Dean et al., 2024) and are prone to significant levels of viral infection and lysis (e.g., Vincent et al., 2023, doi: 10.1038/s41467-023-36049-3) severely questions how valid this assumption is.
[Response]: Thank you for pointing out this important issue. We acknowledge that assuming 100% of coccolithophore production is exported out of the euphotic zone is an oversimplification.
Lns 412 and 414, Introducing totally new concepts (TA*-CFC age-based RTA, Alk*-TTD 14C age based-RTA) at this (late) stage of the article (i.e., concepts not mentioned in the introduction) makes this section of the discussion very confusing and difficult to follow. That these important points are only covered in 4 lines also leaves little room to fully explore them.
[Response]: Please refer to the response in the “general comments” section. The details of calculations related to the water column tracer Alk*, which were originally included in the supplementary material, have also been removed.
Lns 416-417, Is this self-validation? If the model did not assume that all production is exported (c.f. POC production), that all oxygen is consumed and that marine snow or faecal pellet sinking speeds are unlikely to be as slow as 10 m d-1, what conclusions do this lead to? Do the authors have data to support the assumptions (e.g., amount of CaCO3 production exported, characteristics of sinking particles in terms of marine snow or faecal pellets, sinking speeds, oxygen gradients in porous marine snow) in the model that validates them? Could their result be interpreted in a different way if CaCO3 dissolution occurs via the metabolic activity of zooplankton? Does their model rule out grazing as a contributor to CaCO3 dissolution or does it just assume that it doesn’t occur?
[Response]: Thank you for your insightful suggestions. In the original manuscript, we had considered scenarios that not all CaCO3 production is exported, allowing for varying export fractions. However, this part has been removed during the revision. The sinking speed of 10 m d⁻1 was applied according to Subhas et al. (2023), which clearly warrants validation by sediment trap data. While our current model does not explicitly include zooplankton grazing as a contributor to shallow CaCO3 dissolution, its significance cannot be ruled out. Please also refer to the response in the “general comments” section.
Ln 420, Figure 10 – Panel (a) is relatively easy to see, though it would be good to see an exploration of sinking speeds between 10 and 100 m d-1 (e.g., 50, 75 m) and some comparison with the literature on particulate sinking speeds of marine snow and fecal pellets (e.g., see Jansen et al., 2002 who conclude ‘respiration-driven dissolution of calcite in the water column seems to be unlikely as the size, settling velocity and porosity of marine snow aggregates are unfavourable for creating a microenvironment with gradients sufficient to convert an oversaturated bulk environment into a locally undersaturated state.’). Please include more discussion of the factors involved than citing only one side of the debate (e.g., Jansen and Wolf-Gladrow, 2001). However, note that Jansen and Wolf-Gladrow (2001) conclude that ‘up to 70% of the ingested carbonate maybe be dissolved in the guts’ in non-bloom situations – could the authors explain where the 25% in line 437 is from? Panel (b) is extremely difficult to understand, for example why are the depths now in density and how does this relate to panel (a) are the densities for the other points the same, how do the lines where no data points included relate in depth to the discrete measurements?
[Response]: Figure 10 has been removed in the revised manuscript. Jansen and Wolf-Gladrow (2001) suggested that up to 70% of the ingested carbonate may be dissolved in the zooplankton gut, and this dissolution process may account for 23% of the total shallow CaCO3 dissolution amount (Milliman et al., 1999). They discussed this value in the section of “contribution to calcite water column dissolution”.
Ln 430, Subhas et al (2022) do not fully agree with the present study; instead finding that ‘a combination of dissolution due to zooplankton grazing and microbial aerobic respiration within degrading particle aggregates’ lead to shallow metabolically driven dissolution. Subhas et al. (2022) also point out that the dissolution of high-Mg carbonates is not necessary to drive shallow dissolution. This is not reflected in lines 434-436. Further, the single comment from Jansen and Wolf-Gladrow (2001) does little justice to the existence of multiple dissolution pathways (especially noting as above that this reference concludes that up to 70% of ingested carbonate may be dissolved through zooplankton ingestion).
[Response]: Subhas et al. (2022) suggested the potential role of zooplankton grazing in metabolically-driven shallow dissolution; however, their model does not explicitly account for this process. Similarly, while this removed section tried to emphasize the role of metabolic processes in shallow CaCO3 dissolution, we acknowledge that our estimations ignored the potential influence of zooplankton ingestion and high-Mg carbonates.
Overall based on your both general and specific comments on the dissolution part, we have decided to remove this entire section to streamline the manuscript focusing on coccolithophore species, PIC concentrations and CaCO3 production. Your insightful suggestions will be incorporated into our future research.
Ln 452, Data Availability - The authors need to provide a more direct link to the relevant data from the article than the general landing page for the Science Data Bank.
[Response]: we have now included a more direct link of https://www.scidb.cn/en/s/i6bMFn in the “Data Availability” section.
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AC2: 'Reply on RC1', Minhan Dai, 10 Feb 2025
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RC2: 'Comment on egusphere-2024-3492', Chloe Dean, 20 Dec 2024
Review of “Pelagic coccolithophore production and dissolution and their impacts on particulate inorganic carbon cycling in the western North Pacific” by Han et al.
The authors clearly demonstrate the substantial contribution of coccolithophores to the production of calcium carbonate standing stocks in the western North Pacific through their presentation of both Niskin bottle and size fractionated PIC measurements, as well as coccolithophore cell abundances, species compositions and diversity. The importance of metabolically driven calcite dissolution is then illustrated through the use of a simple box model, which builds upon previous studies by incorporating published data for regenerated total alkalinity and PIC flux. The results presented in this paper build upon similar studies (Ziveri et al., 2023, Subhas et al., 2022), and also integrate emerging methodologies and ideas for investigating the calcium carbonate cycle. In particular, biologically driven dissolution within the supersaturated “shallow” ocean is a quickly emerging mechanism which is helping to constrain the long-standing discrepancy between calcium carbonate production and export. Broadly, I am impressed by how the author’s weaved together multiple lines of evidence to understand coccolithophores' role in the calcium carbonate cycle, especially through the lens of coccolith calcite production and dissolution. To that end, I have a few comments which I hope will help to strengthen the manuscript and improve the scope of the content.
The authors do a fairly thorough job of describing their assumptions, and for the most part, clarify how these translate into uncertainty within their analysis. There are a few assumptions in particular which I believe could be more thoroughly justified by the authors, 1) the assumption that satellite data underestimates PIC standing stocks, 2) the use of a range of reported PIC turnover times, and 3) the assumptions around PIC content of coccoliths, and the discussions around free liths vs coccospheres.
For the satellite imagery statement (lines 65-66) I am suggesting that you add a citation from Neukermans et al., 2023, which provides direct evidence for the discrepancy you are pointing out here. Additionally, given this stated uncertainty in satellite estimates of [PIC], I found it confusing to follow the author's justification of using satellite derived [PIC] (both from July 2022 and annual mean) to correct the PIC production rates for seasonal variability (lines 131-133). I would appreciate some commentary from the authors regarding their justification for this, for example, similar to the Supplementary Figure 2 from Ziveri et al., 2023, which illustrates the correction factor between satellite estimates and direct measurements of PIC for a given region.
With regards to the use of the reported range of turnover times, I think it would be worthwhile for the authors to comment on the large uncertainty that this method results in (i.e. the high production tails in Fig. 6b that stem from the order of magnitude range in turnover time estimates [0.7-10 days; Lines 124-126]), and how it may hinder interpretation of this field data. There are currently a few methods which can get at in situ turnover time, primarily the use of carbon isotopes spikes in incubations, with the carbon-14 method described in Graziano et al., 2000. While I completely understand that it is not possible to do this for this study, I do think it would be helpful for the authors to acknowledge that direct measurements of turnover time could have likely reduced uncertainty within the PIC production values. Especially when considering the challenges around quantifying the oceanic calcium carbonate budget, any advancements in our ability to reduce error and uncertainty should be at the fore-front of our minds.
The author’s use of average coccolith/coccosphere calcite to calculate out the PIC inventory and PIC production rates could warrant more discussion on uncertainty and in general, the nuances of these assumptions. My concerns around this approach stem from the fact that Johns et al., 2023 clearly showed that the production and subsequent cycling of free coccoliths can be rapid and complex. Using a generalized [PIC] quota for each species of coccolithophore will not capture the dynamics of coccolith reabsorption, and I would suggest the authors acknowledge this. Additionally, in Lines 325-327, the authors state that “detached coccolith concentrations of… showed a significant positive relationship with their coccosphere cell concentrations, indicating that those detached particles were likely to have originated from living cells”. This statement is a bit misleading, as it supposes that free liths are only coming from cells that are no longer alive. I suggest modifying in consideration of the Johns et al 2023 paper, which shows that lith shedding is a dynamic process throughout the cell's life cycle. In general, I would like the authors to comment further on the dynamics of coccolith production and shedding (i.e. how it changes with dominant species shifts, how it may be depth dependent and subsequent consequences to different dissolution processes [particle vs gut], etc).
While the author's presentation of the environmental data and its influence on the coccolithophore community structure is certainly an interesting and impressive data set, I feel that it generally distracts the reader from the main goals of this manuscript. Given that the title is “Pelagic coccolithophore production and dissolution and their impacts on particulate inorganic carbon cycling in the western North Pacific”, I think the authors should stick to these research aims in the manuscript, and either try to weave the environmental aspects of the study more broadly throughout the manuscript, or consider presenting the environmental-drivers as a follow-on manuscript.
I appreciate the author's approach to assessing the role of metabolically driven dissolution, as this is an emerging mechanism impacting the shallow calcium carbonate cycle that has major implications for the field. I have some suggestions for interpreting the box-model dissolution output against previously reported observations of alkalinity regeneration (presented in Fig 10b). I was surprised the authors did not comment on the mismatch between the maxima of alkalinity regeneration between observations and model output. The observations show a clear peak alkalinity regeneration well above 500m, whereas the model output shows the peak occurring at or near 500m. I believe this mismatch is due to unique “metabolic” processes that occur at different depths in the water column. For example, micro- and macro-zooplankton primarily graze within that upper 500m, and therefore, could be the primary drivers of that shallow alkalinity regeneration due to calcium carbonate dissolution during ingestion and digestion processes. A recently published paper (Dean et al., 2024) titled provides experimental evidence that microzooplankton facilitate a substantial amount of coccolith calcite dissolution through grazing and digestion. I bring this up, because the model, and broader context of this discussion, is largely focused on particle associated metabolic dissolution. If the authors were to consider the different types of metabolic dissolution that occur at different depths in the water column, they may be able to directly comment on the maxima mismatches in Fig 10b and provide a stronger discussion for section 4.4. This is an active area of research which warrants a deeper discussion from the authors.
Overall, there is a lot of valuable and needed field data being presented in this manuscript which certainly contributes to our understanding of calcium carbonate cycling dynamics, especially as driven through coccolithophores. My overall suggestion to the authors is to really hone in the scope of this manuscript, and keep the focus to coccolith calcite production and dissolution. The environmental data, while incredibly interesting, could enhance the scope of this study if integrated into the discussion further, or would serve well being presented independently as a follow-on study.
Additional minor comments:
- I might suggest modifying the title to be “Coccolithophore production and dissolution and their impacts on pelagic particulate inorganic carbon cycling in the western North Pacific”, given that “pelagic” is really in reference to the depths of PIC cycling, and not coccolithophore PIC production, which is always pelagic.
- Line 59, could expand from just “zooplankton” to “micro and meso zooplankton”. Could also add a citation for my recent publication (Dean et al., 2024) which provides direct experimental evidence for microzooplankton facilitated dissolution, and shows that microzooplankton food vacuoles are acidic and eventually buffered from coccolith calcite dissolution.
- Citation for lines 65-66, regarding satellite PIC and measured/integrated PIC discrepancies?
- Suggestion is Neukermans et al., 2023 (see end of review for reference list)
- Line 119-120: Considerations around using an average coccolith calcite mass and potential error?
- While most other stated assumptions are followed with a comment on the uncertainty they bring, I found this assumption to be not acknowledged at the same level as others. Would suggest adding a statement which at least speculates on the uncertainty this is adding to your calculations. For example, different coccolithophore species have very differing growth rates, and consequently, different PIC production rates/turnover times. Given the marked differences in coccolithophore species composition reported in this study, I believe the authors should expand upon this section.
- Line 230-231: Clarification Question, is this in reference to all E. huxleyi associated calcite (i.e. coccospheres and liths)? Or just coccospheres?
- Fig 5.
- Suggestion for readability: Add labels to the pie charts to make it easiest to compare coccosphere to liths to total calcite
- Line 243: Why a depth of 150m for standing stock integration? I don’t think this was stated in the methods or results. Can you comment on the implications of setting the same depth for this integration?
- Fig 6b.
- I had never seen a violin plot before, so it was a bit difficult for me to interpret this figure on my first pass. I would suggest that the authors provide additional description in the caption to at least describe what the blue diamond, blue line, and shape of the plots represent.
- Line 292: RDA has not been previously defined. Only defined in Fig. 7 caption, so you may want to define it in the text. Additionally, I think the authors could provide additional justification for their choice in using RDA for this study. I would suggest adding this in the methods section, so that someone who is less familiar with multivariate analyses can understand why this is appropriate here.
- Fig 8a.
- Clarifying, does coccolithophore calcite = coccosphere and coccoliths? Or just coccosphere?
- Line 333: what is the “aggregation group”? Can you please explain further?
- Lines 339-341: “Thus, although E. huxleyi is one of the most abundant species in the ocean, larger coccolithophore species can also play an important role in CaCO3 export.”
- I would like the authors to provide some justification for this statement from the data presented in this manuscript. It seems that Fig 5. Could be modified to illustrate this point, perhaps by adding percentages and errors to the pie charts?
- I don’t think Fig 5 does a good job of illustrating this point, since they are grouped into the “other” category. I would suggest having a supplementary figure which shows the contributions of these larger species to the total inventory, so that you might reference them in this statement.
- Line 345-347: Does this need a citation?
- With respect to the DCM being deeper than 100m in subtropical gyres
- Lines 347-348: Can the authors provide a value or range of values for the underestimation here?
- Lines 369-372: Did the authors look at any metrics for the composition of the non-coccolithophore community members? Since there is a point here about competition, and the authors did such a thorough job of investigating the coccolithophore diversity, it would be interesting to extend that thought to the results of this study.
- Line 394: “high dynamics” seems vague to me, but perhaps I’m misinterpreting this?
- Line 401: I believe there is a typo in this sentence? “The results suggest that CaCO3 might start to dissolve in “setting” marine particles after sinking out of the…” Should “setting” be “settling”?
- Line 436-437: Could cite my recent publication (Dean et al 2024) to show that MZP also contributes substantially to dissolution in lab study.
References
Dean, C.L., Harvey, E.L., Johnson, M.J., Subhas, A.V. Microzooplankton grazing on the coccolithophore Emiliania huxleyi and its role in the global calcium carbonate cycle. Science Advances, 10 (2024).
Graziano, L.M., Balch, W.M., Drapeau, D., Bowler, B.C., Vaillancourt, R., Dunford, S. Organic and inorganic carbon production in the Gulf of Maine. Continental Shelf Research, 20 (2000).
Johns, C.T., Bondoc-Naumovitz, K.G., Matthews, A., Matson, P.G., Iglesias-Rodrigues, D.M., Taylor, A.R., Fuchs, H.L., Bidle, K.D. Adsorptive exchange of coccolith biominerals facilitates viral infection. Science Advances, 9 (2023).
Neukermans, G., Bach, L.T., Butterley, A., Sun, Q., Claustre, H., Fournier, G.R. Quantitative and mechanistic understanding of the open ocean carbonate pump - perspectives for remote sensing and autonomous in situ observation. Earth-Science Reviews, 239 (2023).
Citation: https://doi.org/10.5194/egusphere-2024-3492-RC2 -
AC1: 'Reply on RC2', Minhan Dai, 10 Feb 2025
Response to reviewers
We thank the reviewers for their detailed comments that helped to significantly improve the manuscript. For your convenience, reviewer comments are presented below in black font, followed by our answers in blue font.
Reviewer #2
The authors clearly demonstrate the substantial contribution of coccolithophores to the production of calcium carbonate standing stocks in the western North Pacific through their presentation of both Niskin bottle and size fractionated PIC measurements, as well as coccolithophore cell abundances, species compositions and diversity. The importance of metabolically driven calcite dissolution is then illustrated through the use of a simple box model, which builds upon previous studies by incorporating published data for regenerated total alkalinity and PIC flux. The results presented in this paper build upon similar studies (Ziveri et al., 2023, Subhas et al., 2022), and also integrate emerging methodologies and ideas for investigating the calcium carbonate cycle. In particular, biologically driven dissolution within the supersaturated “shallow” ocean is a quickly emerging mechanism which is helping to constrain the long-standing discrepancy between calcium carbonate production and export. Broadly, I am impressed by how the author’s weaved together multiple lines of evidence to understand coccolithophores' role in the calcium carbonate cycle, especially through the lens of coccolith calcite production and dissolution. To that end, I have a few comments which I hope will help to strengthen the manuscript and improve the scope of the content.
[Response]: We thank Reviewer #2 for the positive and constructive feedback. We have fully considered these comments and suggestions in the revision.
The authors do a fairly thorough job of describing their assumptions, and for the most part, clarify how these translate into uncertainty within their analysis. There are a few assumptions in particular which I believe could be more thoroughly justified by the authors, 1) the assumption that satellite data underestimates PIC standing stocks, 2) the use of a range of reported PIC turnover times, and 3) the assumptions around PIC content of coccoliths, and the discussions around free liths vs coccospheres.
For the satellite imagery statement (lines 65-66) I am suggesting that you add a citation from Neukermans et al., 2023, which provides direct evidence for the discrepancy you are pointing out here. Additionally, given this stated uncertainty in satellite estimates of [PIC], I found it confusing to follow the author's justification of using satellite derived [PIC] (both from July 2022 and annual mean) to correct the PIC production rates for seasonal variability (lines 131-133). I would appreciate some commentary from the authors regarding their justification for this, for example, similar to the Supplementary Figure 2 from Ziveri et al., 2023, which illustrates the correction factor between satellite estimates and direct measurements of PIC for a given region.
[Response]: We appreciate your suggestions and have added the citation into the revised manuscript “This contrast, however, is smaller than the sixfold to sevenfold difference based on satellite estimates of surface PIC, indicating the importance of coccolithophore CaCO3 production over a deeper euphotic zone and the limitations of satellite products as highlighted by Neukermans et al. (2023)”.
We agree that satellite-derived PIC does not accurately represent PIC production throughout the water column. However, using satellite-derived PIC concentrations for seasonal correction is based on the following reasons: (1) PIC production (coccolithophore production) exhibits significant seasonal variability, especially in transitional regions. Since our sampling was conducted only during the summer, it does not capture year-round production. Therefore, the seasonal corrections are essential to better represent annual patterns. (2) Although satellite-derived PIC primarily reflects PIC concentrations in the upper few meters of the water column, the relative seasonal and inter-annual variations observed at the surface broadly reflect those at depth (Neukermans et al., 2023; Ziveri et al., 2023). Therefore, they support the use of satellite-derived PIC concentrations for relative seasonal corrections, even though the absolute values may not fully represent the PIC production throughout the water column.
In response to your suggestion, we have referred to Ziveri et al. (2023), and added a supplementary figure to illustrate the correction factor between satellite-derived estimates and direct measurements of PIC for the given region.
We have clarified this issue in our revision by “Overall, our results suggest that the calibration of satellite-derived PIC is not reliable. There was a significant positive relationship between surface coccolithophores calcite concentrations and satellite-derived PIC concentrations (r2 = 0.84; p < 0.01), which means satellite-derived PIC can reflect the distribution tendency of coccolithophore calcite concentrations but not the true values (satellite-derived PIC in high latitude area is likely overestimated, Fig S5a). Over the entire euphotic zone, our results indicate no correlation between satellite-derived PIC concentrations and actual PIC production, a finding that is also highlighted in Ziveri et al. (2023), in which the linear correlation is primarily driven by the highest data values (Fig. S5b).”
Revised Fig. S5. Scatter plots showing relationships (a) between surface coccolithophores calcite concentrations and satellite-derived particulate inorganic carbon (PIC) concentrations; (b) between coccolithophores CaCO3 production rate (not seasonal corrected) in the euphotic zone and satellite-derived PIC concentrations. The red marks are data from the CDisK-IV cruise and the CaCO3 production rate only includes contributions from coccolithophores (Ziveri et al., 2023).
With regards to the use of the reported range of turnover times, I think it would be worthwhile for the authors to comment on the large uncertainty that this method results in (i.e. the high production tails in Fig. 6b that stem from the order of magnitude range in turnover time estimates [0.7-10 days; Lines 124-126]), and how it may hinder interpretation of this field data. There are currently a few methods which can get at in situ turnover time, primarily the use of carbon isotopes spikes in incubations, with the carbon-14 method described in Graziano et al., 2000. While I completely understand that it is not possible to do this for this study, I do think it would be helpful for the authors to acknowledge that direct measurements of turnover time could have likely reduced uncertainty within the PIC production values. Especially when considering the challenges around quantifying the oceanic calcium carbonate budget, any advancements in our ability to reduce error and uncertainty should be at the fore-front of our minds.
[Response]: We agree that the wide range of turnover times highly likely induces the uncertainty in our PIC production estimates, and field-based measurements of calcification rates could provide more direct and accurate value.
We have added a discussion in the revised manuscript: “While 14C incubations can provide a direct and precise measurement of in situ calcification rates, the calculation method we used offers a practical approach to convert concentration data into production estimates using turnover time (Graziano et al., 2000; Ziveri et al., 2023). This approach has limitations, particularly due to uncertainties in the estimation of coccolithophore calcite, which relies on cell counts and a morphometric-based calcite estimation method, with potential errors reaching up to 50% (Young and Ziveri, 2000b; Sheward et al., 2024). Furthermore, the calculation of production rates introduces further uncertainty, as it depends on the coccolithophore calcite standing stock and a broad range of turnover time estimates. Despite these challenges, this method produces reasonable results that are comparable to field observations and thus helps fill a critical data gap in the study region.”
We have also added a sentence stating that: “In addition, more in situ calcification rate determined by 14C incubations experiments as well as direct measurements of turnover time are required to reduce uncertainty in PIC production estimations and would help in the assessment of the oceanic calcium carbonate budget.”
The author’s use of average coccolith/coccosphere calcite to calculate out the PIC inventory and PIC production rates could warrant more discussion on uncertainty and in general, the nuances of these assumptions. My concerns around this approach stem from the fact that Johns et al., 2023 clearly showed that the production and subsequent cycling of free coccoliths can be rapid and complex. Using a generalized [PIC] quota for each species of coccolithophore will not capture the dynamics of coccolith reabsorption, and I would suggest the authors acknowledge this. Additionally, in Lines 325-327, the authors state that “detached coccolith concentrations of… showed a significant positive relationship with their coccosphere cell concentrations, indicating that those detached particles were likely to have originated from living cells”. This statement is a bit misleading, as it supposes that free liths are only coming from cells that are no longer alive. I suggest modifying in consideration of the Johns et al 2023 paper, which shows that lith shedding is a dynamic process throughout the cell's life cycle. In general, I would like the authors to comment further on the dynamics of coccolith production and shedding (i.e. how it changes with dominant species shifts, how it may be depth dependent and subsequent consequences to different dissolution processes [particle vs gut], etc).
[Response]: We agree that although the method for estimating coccolithophores calcite has been widely applied in many oceanic regions including the Atlantic Ocean, the Southern Ocean, and the South China Sea (Broerse et al., 2000; Jin et al., 2016; Rigual Hernández et al., 2020; Jin et al., 2022), it does have certain uncertainties, primarily from cell counts and the calcite content of specific coccolithophore species.
We have acknowledged this in our revision by stating that “We also acknowledge that estimating coccolithophore calcite and production rates using an average coccolith calcite value introduces uncertainties, as this approach does not fully account for the complexities of coccolith dynamics, including rapid cycling and reabsorption (Johns et al., 2023).”
Based on your suggestions, we have revised the relevant sentences in the revised manuscript as “It is noteworthy that detached coccolith concentrations of E. huxleyi, U. tenuis and Syracosphaera spp. showed a significant positive relationship with their coccosphere cell concentrations (Fig. 7b–d), indicating that these detached particles were likely shed by cells as part of the dynamic calcification process, where coccoliths are continuously produced and released (Johns et al., 2023). However, other potential sources and processes, such as advection, cell disintegration from viral lysis and grazing, fecal pellets, or the dissolution associated with microbial respiration could also contribute to the observed detached coccolith concentrations (Vincent et al., 2023; Subhas et al., 2022; Dean et al., 2024). Coccolith production and shedding are dynamic processes, with fast-growing species like E. huxleyi producing and shedding coccoliths rapidly during exponential growth phases, whereas other species exhibit different patterns, which are influenced by their distinct physiological and ecological characteristics (Johns et al., 2023).”
While the author's presentation of the environmental data and its influence on the coccolithophore community structure is certainly an interesting and impressive data set, I feel that it generally distracts the reader from the main goals of this manuscript. Given that the title is “Pelagic coccolithophore production and dissolution and their impacts on particulate inorganic carbon cycling in the western North Pacific”, I think the authors should stick to these research aims in the manuscript, and either try to weave the environmental aspects of the study more broadly throughout the manuscript, or consider presenting the environmental-drivers as a follow-on manuscript.
[Response]: Thank you for your insightful feedback on the manuscript’s aims and structure. Considering the recommendations from Reviewer #1, we have reorganized the discussion section to streamline the scope of the paper focusing on coccolithophore calcite production. As a result, we have removed Section 4.4 on shallow-water dissolution of CaCO3. The revised discussion section is as follows:
4.1 Contribution of coccolithophore calcite to PIC
4.2 Coccolithophore responses to environmental factors (Per your suggestion, we have weaved the environmental aspects more broadly. Please also see our response to relevant comments by Reviewer #1)
4.3 CaCO3 production compared with the eastern North Pacific
I appreciate the author's approach to assessing the role of metabolically driven dissolution, as this is an emerging mechanism impacting the shallow calcium carbonate cycle that has major implications for the field. I have some suggestions for interpreting the box-model dissolution output against previously reported observations of alkalinity regeneration (presented in Fig 10b). I was surprised the authors did not comment on the mismatch between the maxima of alkalinity regeneration between observations and model output. The observations show a clear peak alkalinity regeneration well above 500m, whereas the model output shows the peak occurring at or near 500m. I believe this mismatch is due to unique “metabolic” processes that occur at different depths in the water column. For example, micro- and macro-zooplankton primarily graze within that upper 500m, and therefore, could be the primary drivers of that shallow alkalinity regeneration due to calcium carbonate dissolution during ingestion and digestion processes. A recently published paper (Dean et al., 2024) titled provides experimental evidence that microzooplankton facilitate a substantial amount of coccolith calcite dissolution through grazing and digestion. I bring this up, because the model, and broader context of this discussion, is largely focused on particle associated metabolic dissolution. If the authors were to consider the different types of metabolic dissolution that occur at different depths in the water column, they may be able to directly comment on the maxima mismatches in Fig 10b and provide a stronger discussion for section 4.4. This is an active area of research which warrants a deeper discussion from the authors.
[Response]: Thank you for pointing out the important issue of the mismatch between observations and model outputs in Fig. 10b. The observations represent alkalinity regeneration over a broad latitudinal range of 30°N–45°N, while the model results are specifically derived from two stations around 40°N. This geographic difference may partially account for the mismatch. Additionally, while the two isopycnal surfaces (𝜎𝜃=26.1 and 26.5) correspond to different densities, they are both situated at approximately 300 m, indicating that the maxima of alkalinity regeneration are geographically and vertically close. However, we agree that density-specific metabolic processes, particularly macro-zooplankton grazing and digestion, play an important role in driving shallow CaCO3 dissolution, whereas zooplankton grazing and free coccolith contributions were not explicitly included in our model.
Please note that mainly based on Reviewer #1’s suggestions, we have removed this entire dissolution section in the revised manuscript. However, your insightful comments on this part will be incorporated into our future research.
Overall, there is a lot of valuable and needed field data being presented in this manuscript which certainly contributes to our understanding of calcium carbonate cycling dynamics, especially as driven through coccolithophores. My overall suggestion to the authors is to really hone in the scope of this manuscript, and keep the focus to coccolith calcite production and dissolution. The environmental data, while incredibly interesting, could enhance the scope of this study if integrated into the discussion further, or would serve well being presented independently as a follow-on study.
[Response]: We greatly appreciate your recognition of the value of the field data presented in our manuscript and its contribution to understanding CaCO3 cycling driven by coccolithophores.
Comprehensively considering comments from both reviewers, we have reorganized the manuscript to focus on coccolithophore calcite production, mainly by removing the section of shallow-water dissolution of CaCO3 and strengthening the discussion regarding environmental data.
Additional minor comments:
- I might suggest modifying the title to be “Coccolithophore production and dissolution and their impacts on pelagic particulate inorganic carbon cycling in the western North Pacific”, given that “pelagic” is really in reference to the depths of PIC cycling, and not coccolithophore PIC production, which is always pelagic.
[Response]: “Pelagic” has been removed. The new title is “Coccolithophore abundance and production and their impacts on particulate inorganic carbon cycling in the western North Pacific”.
- Line 59, could expand from just “zooplankton” to “micro and meso zooplankton”. Could also add a citation for my recent publication (Dean et al., 2024) which provides direct experimental evidence for microzooplankton facilitated dissolution, and shows that microzooplankton food vacuoles are acidic and eventually buffered from coccolith calcite dissolution.
[Response]: We have removed this paragraph due to the removal of Section 4.4, as Reviewer #1 suggestion.
- Citation for lines 65-66, regarding satellite PIC and measured/integrated PIC discrepancies?
Suggestion is Neukermans et al., 2023 (see end of review for reference list)
[Response]: The citation of Neukermans et al. (2023) has been added.
- Line 119-120: Considerations around using an average coccolith calcite mass and potential error?
While most other stated assumptions are followed with a comment on the uncertainty they bring, I found this assumption to be not acknowledged at the same level as others. Would suggest adding a statement which at least speculates on the uncertainty this is adding to your calculations. For example, different coccolithophore species have very differing growth rates, and consequently, different PIC production rates/turnover times. Given the marked differences in coccolithophore species composition reported in this study, I believe the authors should expand upon this section.
[Response]: Based on your suggestion, we have added the following statement in the revised manuscript:
- Methods section: “The coccolithophore turnover time was derived from both laboratory and field estimates, as well as simulations from a generalized coccolithophore model, which has also been applied to the eastern North Pacific (Krumhardt et al., 2017; Ziveri et al., 2023). We are aware that different coccolithophore species exhibit widely varying growth rates, and cell growth phase differs for smaller cells produce fewer coccoliths during the exponential growth phase (characterized by rapid division), whereas larger cells generate more coccoliths during the early stationary phase, when cell division slows down (Raven and Crawfurd, 2012; Krumhardt et al., 2017). We also acknowledge that estimating coccolithophore calcite and production rates using an average coccolith calcite value introduces uncertainties, as this approach does not fully account for the complexities of coccolith dynamics, including rapid cycling and reabsorption (Johns et al., 2023). Despite these possible errors and uncertainties, our estimations are consistent with direct production rate measurements of Daniels et al. (2018), suggesting that our data provide a reliable basis for assessing coccolithophore calcification dynamics.”
- Discussion section: “While 14C incubations can provide a direct and precise measurement of in situ calcification rates, the calculation method we used offers a practical approach to convert concentration data into production estimates using turnover time (Graziano et al., 2000; Ziveri et al., 2023). This approach has limitations, particularly due to uncertainties in the estimation of coccolithophore calcite, which relies on cell counts and a morphometric-based calcite estimation method, with potential errors reaching up to 50% (Young and Ziveri, 2000a; Sheward et al., 2024). Furthermore, the calculation of production rates introduces further uncertainty, as it depends on the coccolithophore calcite standing stock and a broad range of turnover time estimates. Despite these challenges, this method this method produces reasonable results that are comparable to field observations and thus helps fill a critical data gap in the study region.”
- Line 230-231: Clarification Question, is this in reference to all huxleyiassociated calcite (i.e. coccospheres and liths)? Or just coccospheres?
[Response]: Only E. huxleyi coccospheres here. We have clarified this point by adding “The coccospheres of E. huxleyi”.
- Fig 5. Suggestion for readability: Add labels to the pie charts to make it easiest to compare coccosphere to liths to total calcite.
[Response]: Figure 5 has been redrawn in the revised manuscript.
Revised Fig. 5. Contribution of different coccolithophore groups to coccosphere cell abundance, detached coccolith abundance, and coccolithophore calcite concentration in the upper 300 m of the water column: (a–c) in the North Pacific Subtropical Gyre (NPSG: M30, M32 and M35) and (d–f) in the Kuroshio-Oyashio transition region (KE3, STN41, STN43 and STN45). Lower euphotic zone (LPZ) species include Florisphaera profunda and Algirosphaera robusta.
- Line 243: Why a depth of 150m for standing stock integration? I don’t think this was stated in the methods or results. Can you comment on the implications of setting the same depth for this integration? [Response]: Based on your suggestion, as well as comments from Reviewer #1, we have revised the integration depth from 150 m to the euphotic zone depth as determined by the 0.1% surface PAR. However, this adjustment does not affect the main conclusions.
Please also see our response to relevant comments by Reviewer #1.
- Fig 6b. I had never seen a violin plot before, so it was a bit difficult for me to interpret this figure on my first pass. I would suggest that the authors provide additional description in the caption to at least describe what the blue diamond, blue line, and shape of the plots represent.
[Response]: We have replotted Figure 6 and rewritten the caption for clarification.
Revised Fig. 6. Calcium carbonate (CaCO3) standing stock in the euphotic zone estimated from Niskin bottle particulate inorganic carbon (PIC), total calcite (Cocco) and size-fractionated (large and small fractions indicate > 51 and 1–51 μm, respectively) PIC concentrations (a) at each sampling station and (b) in the North Pacific Subtropical Gyre (NPSG) and Kuroshio-Oyashio transition regions; (c) CaCO3 production by coccolithophores in the euphotic zone at indicated sampling stations in June-July 2022; (d) annual CaCO3 production corrected for seasonal bias using satellite-derived PIC concentrations. The blue diamond marks the median value, while the shaded area displays the probability density of the estimates. The grey lines denote the quartiles (the 25th and 75th percentiles).
- Line 292: RDA has not been previously defined. Only defined in Fig. 7 caption, so you may want to define it in the text. Additionally, I think the authors could provide additional justification for their choice in using RDA for this study. I would suggest adding this in the methods section, so that someone who is less familiar with multivariate analyses can understand why this is appropriate here.
[Response]: We have added the corresponding content in the methods section as “The redundancy analysis (RDA) is a widely used multivariate analytical method to identify relationships among individual variables in different categories. Prior to the RDA, statistical differences in environmental variables were evaluated using an analysis of variance (one-way ANOVA), while collinearity between environmental variables was accounted for by calculating variance inflation factors (VIF). Forward selection of variables was subsequently carried out until all VIF scores were <10, in order to only include variables that are not significantly correlated. These criteria reduced the number of environmental variables used in the RDA. Monte Carlo permutation tests, based on 1000 randomizations, were performed to identify the most significant and independent effects on variation in the composition of the coccolithophore community. The overall significance of the explanatory variables after forward selection was evaluated through ANOVA (α<0.05) and coefficient of determination (r2) and adjusted r2 were calculated to assess the power of a selected RDA model using the vegan package (Oksanen, 2010).”
- Fig 8a. Clarifying, does coccolithophore calcite = coccosphere and coccoliths? Or just coccosphere?
[Response]: Here, coccolithophore calcite refers to the total calcite content, which includes both the calcite within coccospheres and the detached coccoliths. We have clarified this point in our revision.
- Line 333: what is the “aggregation group”? Can you please explain further?
[Response]: In the scanning electron microscope (SEM) analyses, “aggregation groups” refer to clusters formed by multiple coccolithophores grouped together. In the study, we only quantified their abundance but excluded them from coccolithophore calcite calculations, as it is challenging to accurately determine the number of individual coccoliths within these aggregates.
We have added details in the “methods” section as “Aggregates formed by clusters of multiple coccolithophores were quantified in terms of abundance but were excluded from the coccolithophore calcite calculations, mainly due to the difficulty in accurately determining the number of individual coccoliths within the aggregates.”
- Lines 339-341: “Thus, although E. huxleyi is one of the most abundant species in the ocean, larger coccolithophore species can also play an important role in CaCO3”
I would like the authors to provide some justification for this statement from the data presented in this manuscript. It seems that Fig 5. Could be modified to illustrate this point, perhaps by adding percentages and errors to the pie charts?
I don’t think Fig 5 does a good job of illustrating this point, since they are grouped into the “other” category. I would suggest having a supplementary figure which shows the contributions of these larger species to the total inventory, so that you might reference them in this statement.
[Response]: We have revised this figure to better illustrate the differences in the contributions of various coccolithophore groups to coccosphere cell abundance, detached coccolith abundance, and coccolithophore calcite concentration between the NPSG region and the Kuroshio-Oyashio transition region. Percentage values have been added. We have also explicitly included Calcidiscus leptoporus and Oolithotus fragilis in the revised figure. Although these species are less abundant, they contributed significantly to the coccolithophore calcite. We believe these revisions more effectively highlight the role of larger species in CaCO3 production and export.
Additionally, we have revised the text as: “The less abundant (<3 %) species such as C. leptoporus and O. fragilis also made a large contribution to calcite concentrations, accounting for 21 % and 12 % of the coccolithophore calcite concentration in the NPSG region and the Kuroshio-Oyashio transition region, respectively (Fig. 5).”
Please refer to our earlier response regarding the revised Figure 5.
- Line 345-347: Does this need a citation?
With respect to the DCM being deeper than 100m in subtropical gyres
[Response]: The citation of Cornec et al. (2021) has been added.
- Lines 347-348: Can the authors provide a value or range of values for the underestimation here?
[Response]: Sorry, we are unable to provide a specific value or range of values for the underestimation. Instead, we have revised the text to make this point more accurate: “In these oligotrophic and low productivity oceans, a subsurface PIC maximum can develop within the euphotic zone, and the highly variable subsurface PIC concentrations are poorly reflected by satellites, potentially limiting the ability to fully capture coccolithophore contributions.”
- Lines 369-372: Did the authors look at any metrics for the composition of the non-coccolithophore community members? Since there is a point here about competition, and the authors did such a thorough job of investigating the coccolithophore diversity, it would be interesting to extend that thought to the results of this study.
[Response]: While we do not have data on non-calcareous phytoplankton abundances, we have added references of previous studies observing latitudinal gradients in diatom biomass and planktonic foraminifera abundance (Hirata et al., 2011; Sugie and Suzuki, 2017; Taylor et al., 2018). Furthermore, we have included supporting evidence from sediment trap data in the North Pacific, which indicate lower fluxes of planktonic foraminifera, organic matter, and biogenic opal in the subtropical region than in the transitional and subarctic regions (Eguchi et al., 2003). These additions help to better discuss the influence of ecosystem structure on the relative importance of different calcifiers across regions.
- Line 394: “high dynamics” seems vague to me, but perhaps I’m misinterpreting this?
[Response]: We have replaced “high dynamics” with “the complex environmental gradients and variability”.
- Line 401: I believe there is a typo in this sentence? “The results suggest that CaCO3 might start to dissolve in “setting”marine particles after sinking out of the…” Should “setting” be “settling”?
[Response]: Yes, it is a typo. This sentence has been removed.
- Line 436-437: Could cite my recent publication (Dean et al 2024) to show that MZP also contributes substantially to dissolution in lab study.
[Response]: The reference of Dean et al. (2024) has been cited elsewhere necessary in the revised manuscript.
References
Broerse, A. T., Ziveri, P., van Hinte, J. E., and Honjo, S.: Coccolithophore export production, species composition, and coccolith-CaCO3 fluxes in the NE Atlantic (34 N21 W and 48 N21 W), Deep Sea Research II, 47, 1877-1905, https://doi.org/10.1016/s0967-0645(00)00010-2, 2000.
Cornec, M., Laxenaire, R., Speich, S., and Claustre, H.: Impact of mesoscale eddies on deep chlorophyll maxima, Geophysical Research Letters, 48, e2021GL093470, https://doi.org/10.1029/2021GL093470, 2021.
Daniels, C. J., Poulton, A. J., Balch, W. M., Marañón, E., Adey, T., Bowler, B. C., Cermeño, P., Charalampopoulou, A., Crawford, D. W., and Drapeau, D.: A global compilation of coccolithophore calcification rates, Earth System Science Data, 10, 1859-1876, https://doi.org/10.5194/essd-10-1859-2018, 2018.
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Eguchi, N. O., Ujiié, H., Kawahata, H., and Taira, A.: Seasonal variations in planktonic foraminifera at three sediment traps in the subarctic, transition and subtropical zones of the central North Pacific Ocean, Marine Micropaleontology, 48, 149-163, https://doi.org/10.1016/S0377-8398(03)00020-3, 2003.
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