the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 30 Jun 2026
Refined CT-Based Proxy for Foraminiferal Diagenesis Shows Evidence for Shallow Dissolution in North Atlantic Sediment Cores
Abstract. Geochemical reconstructions (e.g., δ18O, Mg/Ca) derived from the shells of the polar and subpolar planktonic foraminifera Neogloboquadrina pachyderma and Neogloboquadrina incompta are foundational to our understanding of high-latitude climate history. However, these species are highly vulnerable to diagenetic alteration—specifically partial dissolution and secondary calcification—which can significantly bias paleoceanographic signals. We introduce nCTDX%, a refined X-ray micro-computed tomography (μCT) proxy designed to quantify foraminiferal diagenesis with increased objectivity and time efficiency. By implementing mathematical thresholding and normalization to a density standard, nCTDX% allows for the direct comparison of shell density across different scans and study sites. Our results from North Atlantic, Nordic Sea, and North Pacific sediment cores confirm that both species dissolve from the inside out, preferentially removing internal structures previously shown to be rich in Mg and leaving behind resistant, low-Mg gametogenic crusts. While core-top nCTDX% correlates with bottom-water carbonate saturation (Δ[CO32-]), we demonstrate that undersaturated pore waters can initiate significant dissolution within the top 2 cm of the sediment column, even at locations where overlying bottom waters are supersaturated. Furthermore, we show that nCTDX% is a sensitive indicator of secondary inorganic overgrowth, which appears in SEM images as low-density rhombohedral crystals on shell exteriors. The potential for pore water dissolution and inorganic calcification to overprint the bottom water Δ[CO32-] signal contained in nCTDX% and other μCT and dissolution-based proxies suggests extreme caution must be taken when they are applied as proxies for bottom water carbonate ion saturation. Instead, given that even partial dissolution of internal shell walls can bias reconstructed temperatures by 1–2 °C, our findings suggest that μCT and dissolution-based proxies are better utilized as indicators of in situ diagenetic state. We therefore advocate for the routine application of nCTDX% to evaluate the preservation state of downcore samples and ensure the fidelity of geochemical paleoclimate records.
- Preprint
(1546 KB) - Metadata XML
-
Supplement
(2379 KB) - BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2026-3333', Anonymous Referee #1, 06 Aug 2026
-
AC1: 'Reply on RC1', Thomas Weiss, 17 Sep 2026
We thank reviewer 1 for their thoughtful, detailed, and constructive review and for noting that our manuscript is well written and represents a meaningful contribution to the field. Given that there are several questions regarding secondary calcification/overgrowth and its appearance in our cross-sectional images, we would like to address them holistically here before responding to each individual comment below.
A central conclusion of our manuscript is that elevated nCTDX% (or CTDX%) values can be driven by both dissolution and secondary inorganic calcification. Consequently, high values cannot be automatically attributed to dissolution alone. Secondary inorganic overgrowths precipitate as smaller, poorly ordered crystals with higher micro- and nano-porosity, which reduces bulk density and yields elevated nCTDX% values.
Our original description of how to distinguish between these two diagenetic processes was unclear, and we apologize for this ambiguity. In the revised manuscript, we clarify that secondary calcification cannot be directly visualized in micro-CT cross-sections because secondary calcite precipitates over existing topographic highs and visually blends with the biogenic test calcite.
Instead, we advocate for a two-step diagnostic workflow:
- Micro-CT Screening: Evaluate micro-CT cross-sections for primary dissolution features (e.g., thin patchy walls, missing internal chamber walls, or elongated inter-lamellar gaps).
- SEM Confirmation: If internal shell structures remain intact despite an elevated nCTDX%, secondary calcification should be suspected and verified using SEM imaging to identify external rhombohedral crystal growth.
We have revised the manuscript to explicitly outline this diagnostic workflow and added explanatory arrows to the SEM figures (Figure 6). Detailed responses to specific reviewer comments follow below.
Reviewer 1
Summary of study
This is a generally well written study presenting microCT scans of subpolar /polar planktic foraminifera species N pachyderma (left and right coiling) (13 samples) and N. incompta (7 samples) from core-tops and sediment cores from the Nordic Seas, subpolar North Atlantic and the North Pacific.
The study builds on previous work which has used the technique of uCT on samples from sites with different Δ[CO32-] values in order to investigate post depositional changes and partial dissolution of the tests of planktic foraminifera. This study is small, but would add new, previously not published species to the knowledge base.
Samples come from a mixture of Atlantic and Pacific core tops (9 samples), where bottom water Δ[CO32-] was between ~ +45 to -13 umol/kg, and down core (to 2 cm) (5) samples. One novel feature of the study is they calculate pore water Δ[CO32-] for the downcore samples. This was always considerably (up to ~30 umol/kg) less than the bottom water, with values of ~+15 to -11 umol/kg.
CT data is presented in the form of a dissolution index, nCTDX%, based on the attenuation values of the scans. The method is based on that of Iwasaki et al. (2022, CTDX%), but modified by using fragments of a standard material (NBS19) to try to standardize where the thresholds of the scan output should be selected. There is an intrinsic problem involved in trying to assess CT scans of foraminifera in that, test wall (particularly if it is partially dissolved), sediment trapped in the test and material reprecipitated inside the test are not completely distinguishable from each other. The method of thresholding used in this index, where there is a cut off for low density material, but the remaining selected pixels are dilated slightly seems a reasonable approach
Conclusions fit generally with previous findings, that inner material of planktic foram tests is the most susceptible to dissolution; that partially dissolved / partially reprecipitated material on the inside of partially dissolved tests shows as low-density material in CT scans; and that environments of Δ[CO32-] below some threshold can be identified with this technique
The methodology seems fine and study aims seem worthwhile. There are some areas which need clarification. The ms is also a bit long for the amount of data presented, it could be made more concise. I put my comments / queries / suggestions to improve the ms below.
Core tops and down core samples
I would like more information about these cores and sites. There are very large differences between calculated Δ[CO32-] of bottom water and pore water, even from sediment shallow in the core (0.5 to 1 cm). Why is this? Is this typical for the average ocean or is it particular to these sites? Are the sites particularly high in organic matter? Do they contain abundant calcite? Are the porewaters anoxic? Is the pH of the porewaters still controlled by carbonate system chemistry, or could it be influenced by acids produced by respiration of organic matter?
Response: We thank the reviewer for raising these fundamental biogeochemical questions regarding our core sites. The porewater dynamics at these stations are central to understanding why porewater Δ[CO32-] departs so significantly from bottom-water values. Full porewater profiles, nutrient data, and solid-phase geochemistry for these stations will be presented in a companion paper (Krishnakumar et al., in prep), which we will cite in the revised text. Below, we address each of your specific queries:
- Why is there such a large difference between bottom water and shallow porewater Δ[CO32-]: The sharp offset between overlying bottom water and shallow porewater (0.5–1 cm) is driven by the rapid aerobic remineralization of organic matter near the sediment-water interface. Microbial respiration releases metabolic CO2 into the interstitial pore fluid, elevating dissolved inorganic carbon (DIC), lowering porewater pH, and suppressing the calcite saturation state. Because both bottom-water and porewater samples were analyzed using identical titrators and procedures on the same day, we rule out analytical artifacts and confirm this is a real environmental gradient.
- Is this typical for the average ocean or particular to these sites? Respiration-driven porewater acidification occurs widely in marine sediments, but its magnitude is particularly pronounced in contourite drift deposits due to high sediment accumulation rates (up to ~60 cm kyr⁻¹). Rapid accumulation buries fresh, labile organic carbon alongside reactive biogenic calcite, trapping metabolic CO2 within fine-grained sediments. Offsets of this magnitude are not unique to our sites; for example, Weldeab et al. (2016) reported porewater Δ[CO32-] reductions of ~40 µmol kg⁻¹ relative to bottom water across tropical and subtropical Atlantic sites.
- Are the sites particularly high in organic matter and abundant in calcite?
a. Organic Matter: Organic matter abundances (LOI550) range from 4.61% to 13.68% across stations. While these values fall within standard benchmark ranges for North Atlantic sediment drifts, the critical factor is the high flux and rapid burial of fresh, labile organic carbon that fuels high aerobic respiration rates near the surface.
b. Calcite Abundance: Yes, solid-phase CaCO3 is abundant across all stations, ranging from ~29% (Station 19) to ~75% (Station 21).
- Are the porewaters anoxic? No, the porewaters in the upper sediment column (0–5 cm) are fully oxic across all stations. Calculated oxygen penetration depths (OPDs) range from 3 cm to 8 cm. Elevated total oxidized nitrogen (approx. 15-35 uM) in these shallow layers confirms active oxic diagenesis and nitrogen oxidation rather than anoxic conditions.
- Is porewater pH controlled by carbonate chemistry or organic matter respiration acids? Porewater pH in the upper centimetres is primarily depressed by metabolic carbonic acid produced via aerobic organic carbon respiration. In the uppermost 0–1 cm, respiration and nitrification consume alkalinity and lower pH. Once porewaters transition to undersaturation, calcite dissolution is initiated, releasing Ca2+ and CO32- into solution. This co-released carbonate buffers the pore fluid against further acidification and establishes positive benthic effluxes of total alkalinity and calcium.
We note as a caveat that full porewater nutrient and trace metal profiles were analyzed specifically for the subpolar North Atlantic stations (Stations 18, 19, 21, and 22; Krishnakumar et al., in prep). While corresponding nutrient/trace metal data are not currently available for the remaining five Nordic Sea stations, these cores exhibit similar sediment characteristics and display comparable porewater carbonate chemistry profiles. We therefore presume that respiration-driven organic matter remineralization is the primary driver of shallow porewater acidification across these sites as well.
We will revise Sections 2.1 and 4.3 of the manuscript to summarize these core site characteristics, explicitly citing Krishnakumar et al. (in prep) for the full porewater geochemical profiles, and clarifying the mechanistic link between respiration-driven acidification and shallow porewater undersaturation.
What were the default values used for total phosphate and total silica? Zero? Is this likely to bias results?
Response: The reviewer is correct that the default input values in CO2SYS are 0 μmol kg-1 for both phosphate and silica when nutrient concentrations are omitted. To confirm that using these default values does not introduce significant bias into our calculated carbonate system parameters, we conducted a sensitivity test on several CTD and multicore porewater samples. For this test, we re-ran calculations in CO2SYS using upper-bound deep-water nutrient values of 3.5 μmol kg-1 for phosphate and 15 μmol kg-1 for silica. The sensitivity analysis confirmed that the impact of omitting nutrient inputs is negligible:
- Calcite saturation state shifted by at most 0.01 across tested samples (and generally showed no change).
- Carbonate ion concentration by <1 µmol kg⁻¹ relative to calculations using default zero inputs.
Because these shifts are far smaller than analytical uncertainty, using the default zero inputs does not bias our calculated Δ[CO32-] values or influence our findings. We will add a statement outlining this sensitivity test to Section 2.2 (Carbonate chemistry) in the revised manuscript.
Actual porewater values came from depth x and then the values were interpolated between that pore water value and bottom water for each sample depth. All the data used to calculate Δ[CO32-] – alkalinity, actual depth of pore-water data, pH– should all be in the Sup Mat.
Response: Great idea. We will add this table to the supplement.
It is stated (line 70) that usually in these kinds of studies it is the Δ[CO32-] of bottom water that is used, not pore-water and this might introduce inaccuracy. In the open ocean, this might be completely fine. It may not be a good assumption for your sites. Say why. This topic needs more discussion.
Response: We agree with the reviewer that assuming porewater carbonate saturation matches overlying bottom water is an unreliable assumption. As detailed in our earlier response regarding core site characteristics, rapid organic carbon burial fuels near-surface aerobic respiration and shallow porewater acidification. The Weldeab et al. (2016) study confirms that large Δ[CO32-] gradients between bottom water and pore water exist across multiple depositional environments in the Atlantic. We therefore advise independent verification that pore waters are not driving dissolution at any site where nCTDX% or CTDX% is to be applied as a proxy for bottom water Δ[CO32-].
We will revise Line 70 in the Introduction to explicitly state why the bottom-water assumption breaks down in high-accumulation drift settings, emphasize that testing this assumption is a central objective of our study, and cite Krishnakumar et al. (in prep) for the detailed geochemical profiling.
Is it concluded that Δ[CO32-] from porewaters fits better with the dissolution index than using bw values? It is never clearly stated
Response: We apologize that this point was not clearly stated. We do not find that either bottom-water or porewater Δ[CO32-] alone forms a perfect relationship with the dissolution index (nCTDX%). Rather, we propose that nCTDX% reflects exposure to the most corrosive conditions the foraminifera encounter. Consequently, undersaturated pore waters beneath supersaturated bottom waters (or vice versa) will complicate a direct calibration to either fluid body. This is why we advocate that nCTDX% should not be applied as a direct proxy for carbonate saturation in bottom or pore waters, but rather as an indicator of overall in situ diagenetic state. We will add clarifying sentences to both the Discussion (Section 4.5) and Conclusion.
NBS19 standard
Say more about this standard. What is it made of? Where did it come from? Why are the particle sizes so different?
Response: We thank the reviewer for requesting further details on the NBS19 standard. Below, we clarify its composition, density properties, and selection rationale:
- Material and Origin: NBS19 (National Bureau of Standards 19) is a crushed white marble reference material prepared by the U.S. Geological Survey (USGS) primarily as a carbonate stable isotope standard (Friedman et al., 1982).
- Grain Size vs. Density Uniformity: Particle sizes are inconsistent because grain size is not critical for stable isotope mass spectrometry, provided individual grains satisfy the mass requirements. We initially intended to use a single grain across all scans to avoid potential size-related density artifacts. However, scanning multiple grains simultaneously revealed that X-ray attenuation/density is uniform across grains regardless of size (Figure S2), consistent with recent findings by Kimoto et al. (2023).
- Selection Rationale: NBS19 was selected because it is a universally recognized reference standard within the paleoceanography community. Although original stocks are depleted from the primary supplier, it remains widely available across paleoceanography stable isotope laboratories.
Manuscript Revision: We will revise Section 2.3 (µCT scanning and image processing) to formally define NBS19, cite Friedman et al. (1982) and Kimoto et al. (2023), and state clearly that grain-size variations do not impact density calibration.
References:
FRIEDMAN, I., O'NEIL, J., CEBULA, G., Two new carbonate stable isotope standards, Geostandards Newsletter 6 1 (1982) 11-12.)
Kimoto K, Horiuchi R, Sasaki O and Iwashita T (2023), Precise bulk density measurement of planktonic foraminiferal test by X-ray microcomputed tomography. Front. Earth Sci. 11:1184671. doi: 10.3389/feart.2023.1184671.
CT is of course a semi-quantitative technique, attenuation intensity of a material depends not only on the material of the sample, but its form (porosity, shape). Then there is some variation in the scanner from day to day, and different scanners no doubt give different values.
Response: We agree with this statement and are in agreement with the rest of the literature that using standards doesn’t make CT fully quantitative but does make it more quantitative.
I was surprised to see that the values of repeated scans of std A shown in Fig S2 are quite so variable. But I also wonder if this is actually a meaningful number. The intensity of the background should be added here. Does it vary in the same way? I would expect that the difference between the background and the standard would be more consistent, and more useful.
Response: We too were surprised to see such variability. Great idea to add the background to Fig S2. We will do this. It varies in the same way, and the reviewer is right in their expectation that the difference between the two is much more consistent. Thankfully, this means that the relationship between relative differences in intensity and density within a scan scale similarly across scan, but it does not mean that absolute intensity will scale well.
The implication is ( line 111 ) that CT gives extremely variable results between scans and that previous studies, which did not use NBS19 standard, used thresholds “visually chosen” for each sample and no attempt was made to provide consistency between samples. This is not the case.
Response: We thank the reviewer for highlighting this ambiguity. We fully agree that prior micro-CT studies routinely incorporate density standards and strive for inter-sample consistency. We do not consider NBS19 to be inherently superior to other carbonate reference materials, though its widespread availability across isotope laboratories is advantageous.
Our intent was not to imply a lack of rigor in previous methodologies, but rather to highlight a specific difference in how normalization anchor points are defined:
- Endpoint Tail-Setting: In the normalization scheme of Iwasaki et al. (2022, 2023), fixed normalized intensity values of 0 and 100 are assigned to the lower and upper tails of individual specimen intensity distributions where pixel counts approach zero. As a result, they are normalizing their intensity values so that the shapes are comparable between samples, but not the absolute densities.
- Peak-Anchoring Scheme: In our refined approach (nCTDX%), normalized anchor values (40 and 60) are tied directly to physical reference peaks, namely, the mean background intensity (air) and the mean peak intensity of the NBS19 standard crystal within each scan. This method allows for better comparison of absolute densities between samples and labs.
We acknowledge that both approaches (as well as normalization directly to air and calibration standards) yield broadly comparable relative density trends across samples.
Manuscript Revisions: We will reword Lines 110–114 in the Introduction to:
- Explicitly clarify that previous studies routinely utilize density standards and established normalization protocols.
- Frame our modified method as an alternative fixed-peak normalization scheme designed to anchor pixel intensities directly to background and standard reference peaks, rather than as a correction of inconsistent visual thresholds.
Line by line comments
Abstract
Add that dissolution index nCTDX% presented here is based on CTDX% (Iwasaki)
Response: Great idea. We will add it.
Add information about number of samples
Response: Another good call and we will add this as well.
Line 21 – how does the refined method add to time efficiency, where is this presented?
Response: Eliminating the need to manually remove sediment when processing images makes the method much more time efficient. This is presented in the methods section and section 4.1. We will make the reasoning clearer in the introduction.
Line 26 – n..% correlates with Δ[CO32-], what is the correlation. Add to discussion and to Conclusion
Response: We do not believe it makes sense to calculate a correlation with so few data points. The relationship also may not be a linear correlation, but instead a threshold. Maybe correlation is not the correct wording for the abstract. We changed correlation to “is a strong indicator of.” Thank you for making this point.
Introduction
Add information about the sites. Why were these sites chosen for investigation, what is special about them
Response: We agree that the manuscript will benefit from a clearer statement of the scientific rationale behind site selection across all our study regions.
These core locations, spanning both the subpolar North Atlantic drift deposits (e.g., Eirik, Björn/Gardar, and Feni Drifts) and the Nordic Seas—were specifically targeted for two key reasons:
- High-Resolution Paleoclimate Archives: All selected sites in both the subpolar North Atlantic and the Nordic Seas are characterized by relatively high sediment accumulation rates. These expanded sedimentary sequences provide the high temporal resolution necessary to reconstruct ocean and climate variability on decadal to centennial timescales.
- Sensitivity to Early Diagenesis: High accumulation settings co-deposit fresh, labile organic carbon alongside reactive biogenic carbonates. Near-surface organic matter remineralization fuels rapid aerobic respiration, making these sites ideal natural laboratories to test whether shallow porewater acidification drives foraminiferal dissolution beneath supersaturated bottom waters
Line 43 – state that foram tests start to dissolve in waters undersaturated wrt calcite, this is not state of the knowledge. They start to dissolve in supersaturated waters, many references for this, some even cited later
Response: Great point. We will reword this sentence to include thresholds from those other citations and add the citations here.
Line 91 – state that (n)CTDX% is a dissolution index and that high values represent less dense partially dissolved material. (Usually for CT the convention is that high values mean more dense material (higher greyscale, lighter colours), so it would be good to clarify for people who might be familiar with CT but not dissolution indices.) Same goes for the figures. Add an arrow to nCTDX% axes to show which direction means better preservation
Response: Very true and good idea. We added clarification here to the text. We also added arrows to figures 5 and 7 indicating more and less dissolution.
Line 105 - the problems of distinguishing between partially dissolved test, trapped sediment and newly crystallising calcite is not only described by Iwasaki et al., (2022), it is mentioned in all studies using CT of forams
Response: While we don’t agree that every study mentions it (we actually think surprisingly few papers mention this in detail), we do agree that more than just Iwasaki et al (2022) do and include more references here.
Methods
Describe orientation of tests in the scanner. It appears random with some on their sides, some aperture up.
Response: Great idea to clarify this. We preferred to attach them on their sides as this made image processing easier, but this was not always easy, so some were aperture up. We will add clarification to the text.
All 8 tests from one sample are scanned together?
Response: Sorry, this wasn’t clear. Yes. This will be clarified in the text.
Section 2.3 image processing (line188)
There are some unexplained initials in this section eg TMX, expand
Response: Thank you for pointing this out. TXM and TXRM are proprietary to Zeiss and don’t have full names. TXM images are the 360 degree projection images of the original scans, while TXRM images are the slices reconstructed from those images (figure 2 b-6 are TXRM images). We will clarify this in the text.
Line 209 – all slices are used to define the background? But all slices will contain std and sample, not just background. Unclear
Response: This is an important point. The previous sentence explains that we isolate each specimen and the standard via cropping. We add the word “isolated” to this sentence to make it clearer.
Line 259 - Authors state they do not want to get rid of pixels lower intensity than the air peak because it comes from beam hardening (softening). What is the advantage of including scan artefacts
Response: We thank the reviewer for raising this point, which allows us to clarify the technical rationale behind defining our normalization boundaries.
The primary advantage of retaining these lower-intensity pixels, rather than clipping the distribution sharply at the mean background (air) level, is to prevent the inadvertent removal of genuine, highly dissolved, or thin shell calcite.
- Physical Cause of Low-Intensity Pixels: In micro-CT scanning at high spatial resolution (0.49 µm), pixels at thin shell margins and along delicate internal structures are subject to localized beam softening and partial volume effects. These physical edge effects can depress the measured X-ray attenuation of real calcite pixels slightly below the mean intensity of the surrounding air background.
- Avoiding Artificial Truncation: If we assigned mean background air to a normalized value of 0 and discarded all pixels below it, we would systematically slice off real, low-density shell structures. This would artificially inflate the measured bulk density of heavily dissolved specimens. Anchoring background air to a normalized value of 40 retains these low-density shell pixels within the 0–100 scale.
- Negligible Volume and Systematic Consistency: Truncating the distribution at a normalized intensity of 0 removes pure background noise while excluding <0.5% of total shell pixels across scans. Because this identical, mathematical boundary is applied uniformly across all specimens, it avoids subjective manual editing and introduces no density bias between thin and thick shells.
Manuscript Revision: We will reword Section 2.3 (µCT scanning and image processing, Lines 258–262) to explicitly explain that retaining pixels below mean air intensity prevents the artificial truncation of genuine thin/dissolved shell margins caused by partial volume effects and beam softening, while confirming that extreme background noise (<0) accounts for <0.5% of total volume.
Line 282 –more details are needed in Sup Mat of how you calculated Δ[CO32-], but I suppose it is meant with respect to calcite (not eg aragonite)
Response: Thank you for pointing out this lack of clarity. In the revised manuscript we clarify in the methods section that it is calcite Δ[CO32-]. We will also clarify that Δ[CO32-] is calculated from omega calcite and in situ calcite saturation.
Results
Does the offset pore and bottom water seem reasonable? Can it be explained
Response: Yes, the offset is physically sound and reflects a real environmental signal driven by rapid near-surface organic carbon remineralization. As the underlying biogeochemical mechanisms and site characteristics are detailed in full in our earlier general response (under Core tops and down core samples), we refer the reviewer to that section. We will cite Weldeab et al. (2016) for literature precedent and Krishnakumar et al. (in prep) for the complete geochemical profiles in the revised text.
Line 312 - All the sample names and results should be in a results table, not just in the sup figs
Response: We will add a table with these data to the supplement. We think this is too much detail to add to the main text, and the individual sample data are in figure 5, so readers can see the sample distribution.
Line 394 – several samples are mentioned by sample name, do they share similar sites / features?
Response: Yes, they are all from the two Pacific stations (i.e. S53MC or S06MC in the name) and they all share these thin elongated gaps.
Discussion
Line 440 - authors mention that N. incompta may be more dissolution susceptible than N. pachyderma because it has higher Mg/Ca. There are several sets of CT scans published for various species. Some from Iwasaki are plotted in Fig 7. Does the observation hold true, does N pachyderma appear have lower dissolution index than tropical species for similar Δ[CO32-] values ?
Response: Great question. Due to our differences in method, this is difficult to evaluate. We are only comparing N. pachyderma and N. incompta in this section.
Line 451 – the reader is directed towards a large figure, need more direction as what is supposed to be seen here
Response: This sentence specifically directs the reader to see the thick shell walls and lack of low-density shell for any samples from stations 21 and 22. The lack of clarity for this example may be that we incorrectly directed the reader to figures S6 and S7 instead of S5 and S7. We apologize for this typo and will fix it in the updated manuscript.
Line 475 – similar to above, make a fig showing what is meant
Response: As noted in our opening response, secondary calcification/overgrowth cannot be directly differentiated from biogenic calcite in micro-CT cross-sections because the secondary calcite precipitates over existing topographic highs and blends with the test wall. Instead, visual confirmation of overgrowth comes directly from Scanning Electron Microscopy (SEM).
Manuscript Revisions:
- Added Annotations to Figure 6: We have revised Figure 6 (SEM images) by adding prominent explanatory arrows to explicitly guide the reader to the secondary rhombohedral calcite overgrowths on specimens from Station 21.
- Text & Callout Clarifications: We have updated the text around Line 475 and Section 4.4 to direct the reader specifically to the annotated SEM panels in Figure 6a–d. We also cross-reference our two-step diagnostic workflow (micro-CT screening for intact internal walls + SEM visual confirmation) detailed in the opening response.
Line 485 – why should time be a factor, and how was it concluded it is not
Response: We thank the reviewer for raising this point, which allows us to clarify the distinction between exposure duration and dissolution kinetics:
- Why Time Could Matter: Because calcite dissolution is a kinetically controlled reaction, longer exposure duration in corrosive (undersaturated) water could, in theory, drive continued mineral loss and yield higher nCTDX% values.
- Why Saturation State Dominates Over Time: In these shallow multicore intervals (0–2 cm), the local saturation state is the primary control on dissolution intensity. Once internal chamber structures undergo initial dissolution, nCTDX% values align directly with the local saturation state rather than continuing to increase with sediment age.
- Empirical Evidence from CT-scans: Across our sites, specimens exposed to equivalent in-situ Δ[CO32-] values exhibit statistically comparable nCTDX% values regardless of sediment depth or accumulation rate (and thus regardless of sediment residence time in the upper 2 cm). Downcore samples at sites with similar porewater saturation states do not show progressively higher dissolution indices than shallower samples under the same saturation conditions.
Manuscript Revision: We will rephrase Section 4.5 (Lines 484–486) to clarify that local in-situ carbonate saturation state, rather than exposure duration or sediment age, is the primary driver of the measured nCTDX% dissolution signal.
Line 492 – high values of dissolution index n..% does not identify between dissolution and diagenetic overgrowth. Preservation should be “evaluate preservation state of the internal walls”. How is this then to be evaluated?
Response: Please see our opening statement that addresses this point.
Section 4.6 (line 521)
This part reads like a literature review. I don’t think it adds to the ms. No geochemical data was measured on these samples so no need to speculate so much.
Response: We acknowledge that this section is long, but we believe our findings have important implications for our understanding of foraminifera geochemistry which was the ultimate goal of this paper. This section also leads into our next publication. We will try to shorten the section for resubmission.
Conclusions
Line 586 – how reliably can you identify tests from sites where Δ[CO32-] < 0 from the index. Looking at fig 7, it is not an exact method.
Response: Yes. We agree that it is not an exact method. The main conclusion of our paper is that the nCTDX% proxy is not a perfect proxy for bottom water carbonate saturation because pore water dissolution or pore/bottom water overgrowth can also result in high values for the proxy.
Was there a better match between the dissolution index and Δ[CO32-] for the core top or the down core data?
Response: The relationship between nCTDX% and in-situ Δ[CO32-] is broadly similar across both core-top and downcore datasets. Rather than reflecting exposure duration or sediment age, nCTDX% tracks the most corrosive conditions the foraminifera encounter, whether in overlying bottom waters or shallow interstitial porewaters.
Manuscript Revision: We will clarify in Section 4.5 and the Conclusion that core-top and shallow downcore samples exhibit a comparable relationship with in-situ saturation state, reinforcing that local carbonate chemistry, rather than time spent dissolving, governs the nCTDX% signal.
Line 595 – states that n..% identifies post deposition precipitation on exterior of test as shown in the sem images (Fig). I do not see convincing evidence of this in the CT scans. If it is there, direct the reader to it with a figure. If by diagenetic overgrowth, it is meant the low density material inside the test which has been described and discussed in previous studies as a partial dissolution feature, then this is different to what Groeneveld 2008 shows, which is precipitation onto well preserved tests.
Response: We completely agree that micro-CT cross-sections do not directly show visual evidence of secondary overgrowth. As outlined in our opening response, secondary calcite precipitates over existing topographic highs and visually blends with the biogenic test calcite in CT scans. Direct visual confirmation of overgrowth comes from SEM imaging (Figure 6)
Manuscript Revisions:
- Line 595 & Text Clarification: We will reword Line 595 and Section 4.4 to clarify that an elevated nCTDX% serves as a quantitative screening indicator for potential diagenetic alteration, which must then be verified via SEM imaging rather than identified directly within micro-CT cross-sections.
- Figure 6 Updates: We have added explanatory arrows to Figure 6 (SEM panels) to directly guide the reader to the rhombohedral overgrowth crystals and reduced extraneous images to focus specifically on these features.
Table 1
Is there a mistake, CE23012?
Response: Yes. Thanks for the catch. This is fixed.
Figures
Fig 4 could go to sup mat
Response: While we do agree that this figure isn’t referenced much in the text, we think it is important to include it in the main text since all of the data is based on this figure and it is convention to include these pictures.
Fig 5 - Adding error bars to each symbol in the legend detracts from clarity
Response: Yes. Good idea. We will make this change for figures 5 and 7
It would be more visually pleasing to place Δ[CO32-] on the y axis and CT on the x axis
Response: While this could be the case, we choose to keep this x and y-axis configuration because it conforms to the precedent set by Iwasaki and others.
Add information to CTDX% scale on y-axis to show in which direction preservation is better or worse
Response: Good idea. We will add this to figures 5 and 7.
Fig 6 – add arrows to guide the reader to the post mortem calcite
Response: Sorry for the lack of clarity. We will make this addition.
Could you show CT scans of the same features
Response: We wish we could, but the secondary calcification features are not visually apparent in CT scans. We make this point on line 459 of the manusctipt and will add a sentence to make it clearer.
Figure 7 – it is stated this data matches well with Iwasaki data. Fig 7 shows data on two different scales. How were the y axes matched up? By assuming similar Δ[CO32-] gave similar index values???
Response: The dual y-axes were aligned by matching the critical diagenetic threshold of each proxy, which is 15 for nCTDX% and approximately 35 for CTDX%. The offset in absolute scale is a methodological artifact: our automated thresholding excludes a small fraction of low-density shell material that manual segmentation retains. Anchoring the threshold baseline sets the vertical alignment, but it does not dictate the slope or spread of the data. The parallel trends across the full Δ[CO32-] spectrum confirm that both proxies capture the same relative diagenetic signal.
Manuscript Revision: We will update the Figure 7 caption and Section 4.5 to explicitly explain that the y-axes are anchored at the diagenetic threshold boundary and clarify how segmentation choices produce the scale offset.
Supplement
Figure S4, S5 add information to scale bar
0 100
less dense – more dense
Response: Good idea. We will add this
What is the white diamond on the scale bar?
Response: We thank the reviewer for pointing this out. The white diamond and colored blocks are internal controls used to manage color scaling in Amira. Because they are extraneous to the figure, we have removed them from all scale bars across the supplementary figures.
“Average station ..DX% increases … right”
does this have some significance? Is there some difference in the stations to the right
Response: No, the stations are ordered in that way for the purpose of making it easier to pick out dissolution patterns.
All the results presented in S6 etc should be in a table
Response: Good suggestion. We will add this.
Citation: https://doi.org/10.5194/egusphere-2026-3333-AC1
-
AC1: 'Reply on RC1', Thomas Weiss, 17 Sep 2026
-
RC2: 'Comment on egusphere-2026-3333', Anonymous Referee #2, 06 Aug 2026
Review “Refined CT-Based Proxy for Foraminiferal Diagenesis Shows Evidence for Shallow Dissolution in North Atlantic Sediment Cores.”
This is an interesting article using X-ray micro-computed tomography to look at diagenesis (dissolution and inorganic secondary calcification).
The paper shows interesting results, confirms (albeit with low sample numbers) the potential effect of undersaturated seawater on core top samples, and that of porewaters on down-core sediment samples.
General comment. nCTDX% forms the main data for this manuscript. While it is interesting to see the summary figures (e.g. figure 5 and 7), it would be helpful to see some of your main inferences evidenced by figures in the main manuscript. For example, in the abstract you write: “Furthermore, we show that nCTDX% is a sensitive indicator of secondary inorganic overgrowth, which appears in SEM images as low-density rhombohedral crystals on shell exteriors.” If this is one of your important conclusions, you need to provide a figure with nCTDX% cross sections showing where this is the case (and where not!) in the profile to the main manuscript. It would also be helpful if you indicated in your supplementary figures which figures show dissolution, which secondary growth and indicate where. It would furthermore be insightful if these figures could then somehow be related to environmental conditions!
Other comments
Line 73 “In addition to partial dissolution, water supersaturated in [CO32-] can also result in diagenesis that influences shell geochemistry.” Replace result in with cause?
Line 120 what does remineralization refer to (do you mean dissolution resulting from low carbonate ion due to remineralisation of organic material?)
Figure 1. Not sure what white symbols refers to (there are purple symbols).
Line 195 Samples size:
It is confusing how the decision regarding minimum sample size was reached by Iwasaki et al. (2022). In their supplementary information they say that test samples were obtained from multiple cores which does not make sense; perhaps multiple samples down-core…
If you look at their a (PS97/114) sample there still is quite a bit variability in st.dev of %low CT volume at a sample number of 15. Iwasaki et al. looked at Globigerina bulloides, whereas here you are looking at other species. To ensure similar conditions apply, it would have been good if you had carried out a similar check.
Section 3.2
Lines 290-292: generalised statement. Is it not possible that the different species have different calcite matrix make-up and thus response differently to in situ ddCO32-? For N.pachyderma it looks like some downcore samples have higher nCTDx%, but not all (different station 3 and 2, where 2 has slightly higher ddCO32-). The baselines look different for the two species, so that for N. incompta one could argue that only station (downcore sample) 19 (with uncertain ddCO32-) is affected by a higher nCTDX%.
Section 3.2
Lines 369-371: these are only a few datapoints; with only one (53MC) showing this (Station 19 has a very wide uncertainty for dd13CO32-). Why do you not comment on N. incompta’s insensitivity to lower carbonate ion? Does this mean it resistant to dissolution?
Please add a figure that shows some clear examples in the article.
Line 428-435: when considering down core samples, you need to consider bioturbation effects, effects of burrows etc as well; some of your specimens could be 200 years, the other thousands of years. And bottom water and pore water carbonate ion concentrations will vary seasonally, in relation to organic carbon flux to the seafloor.
Lines 487-489: please rephrase this. You seem to have different threshold values to the two species, so it will likely be different for other species as well. Plus you cannot be sure that the relationship will be the same in different environments (for example methane seeps).
Lines 576-578: some words missing.
Line 588 basedproxies.
Line 594-594: why do rapid sedimentation rates lead to higher remineralization rates of organic matter? Does it not depend on what the sediment is made out of?
Citation: https://doi.org/10.5194/egusphere-2026-3333-RC2 -
AC2: 'Reply on RC2', Thomas Weiss, 17 Sep 2026
We thank Reviewer 2 for their thoughtful review and for noting the interest of our findings. Because secondary overgrowth and its manifestation in micro-CT versus SEM imaging is also the central theme of your comments, we kindly refer Reviewer 2 to our opening response to Reviewer 1.
In brief, secondary calcification cannot be directly visualized in micro-CT cross-sections and is confirmed via SEM imaging; micro-CT cross-sections serve as the first-line screening tool to verify that internal shell structures remain intact despite elevated nCTDX%. We have revised the manuscript text, figure callouts, and figure annotations (including Figure 6) to make this two-step diagnostic workflow clear. Detailed responses to your individual comments follow below.
Reviewer 2
Review “Refined CT-Based Proxy for Foraminiferal Diagenesis Shows Evidence for Shallow Dissolution in North Atlantic Sediment Cores.”
This is an interesting article using X-ray micro-computed tomography to look at diagenesis (dissolution and inorganic secondary calcification).
The paper shows interesting results, confirms (albeit with low sample numbers) the potential effect of undersaturated seawater on core top samples, and that of porewaters on down-core sediment samples.
General comment. nCTDX% forms the main data for this manuscript. While it is interesting to see the summary figures (e.g. figure 5 and 7), it would be helpful to see some of your main inferences evidenced by figures in the main manuscript. For example, in the abstract you write: “Furthermore, we show that nCTDX% is a sensitive indicator of secondary inorganic overgrowth, which appears in SEM images as low-density rhombohedral crystals on shell exteriors.” If this is one of your important conclusions, you need to provide a figure with nCTDX% cross sections showing where this is the case (and where not!) in the profile to the main manuscript. It would also be helpful if you indicated in your supplementary figures which figures show dissolution, which secondary growth and indicate where. It would furthermore be insightful if these figures could then somehow be related to environmental conditions!
Response: We are sorry this point wasn’t made clear enough. We don’t see the overgrowths in the uCT cross sectional images, only the SEM images. We will add several sentences to the discussion to make this clearer. This point is also covered starting on line 499. The figures in the supplement are related to environmental conditions by including the in-situ Δ[CO3]. We will add arrows and markers indicating dissolution features.
Other comments
Line 73 “In addition to partial dissolution, water supersaturated in [CO32-] can also result in diagenesis that influences shell geochemistry.” Replace result in with cause?
Response: Good idea. We will make this change.
Line 120 what does remineralization refer to (do you mean dissolution resulting from low carbonate ion due to remineralisation of organic material?)
Response: Thank you for pointing this out. We will change remineralization to secondary calcification for clarity
Figure 1. Not sure what white symbols refers to (there are purple symbols).
Response: Thank you for the catch. This was left over from a previous draft and removed.
Line 195 Samples size:
It is confusing how the decision regarding minimum sample size was reached by Iwasaki et al. (2022). In their supplementary information they say that test samples were obtained from multiple cores which does not make sense; perhaps multiple samples down-core… If you look at their a (PS97/114) sample there still is quite a bit variability in st.dev of %low CT volume at a sample number of 15. Iwasaki et al. looked at Globigerina bulloides, whereas here you are looking at other species. To ensure similar conditions apply, it would have been good if you had carried out a similar check.
Response: We completely agree that having more specimens is always better, however, given the minimal overlap between individual specimens from undissolved and dissolved stations, we believe our findings are robust.
Section 3.2
Lines 290-292: generalised statement. Is it not possible that the different species have different calcite matrix make-up and thus response differently to in situ ddCO32-? For N.pachyderma it looks like some downcore samples have higher nCTDx%, but not all (different station 3 and 2, where 2 has slightly higher ddCO32-). The baselines look different for the two species, so that for N. incompta one could argue that only station (downcore sample) 19 (with uncertain ddCO32-) is affected by a higher nCTDX%.
Response: We agree that species can initiate dissolution at slightly different carbonate saturation thresholds due to differences in shell geochemistry (e.g., higher Mg/Ca in N. incompta relative to N. pachyderma). For example, at Station 18, where porewaters straddle saturation (Δ[CO3] approx. 0), N. incompta exhibits evidence of partial dissolution while N. pachyderma remains intact. However, comparing co-occurring specimens of both species across our core sites (Table 1) reveals no systematic baseline offset or consistent relative difference in Δ[CO3] values across the full dataset.
Manuscript Revision: We will add a clarifying sentence to Section 4.3 (Discussion) noting that while species-specific dissolution initiation thresholds can occur near equilibrium (Δ[CO3] approx. 0), both species display comparable relative nCTDX% responses across the broader dataset.
Section 3.2
Lines 369-371: these are only a few datapoints; with only one (53MC) showing this (Station 19 has a very wide uncertainty for dd13CO32-). Why do you not comment on N. incompta’s insensitivity to lower carbonate ion? Does this mean it resistant to dissolution?
Response: We thank the reviewer for this observation and apologize for the lack of clarity in the text. Neogloboquadrina incompta is sensitive to low carbonate saturation. When exposed to undersaturated conditions (e.g., Stations 19, 06MC, 53MC, and Station 18 downcore), N. incompta exhibits distinctly elevated nCTDX% values compared to well-preserved, supersaturated baseline stations like Station 8.1.
The apparent "insensitivity" on summary plots arises because Stations 21 and 22 plot with elevated nCTDX% despite high carbonate saturation, but for two distinct reasons:
Station 21: High nCTDX% is confirmed to be driven by secondary inorganic overgrowth via SEM imaging (Figure 6a–d).
Station 22: We do not have direct SEM proof of overgrowth for Station 22. In fact, companion porewater geochemistry in Krishnakumar et al. (in prep) shows positive calcium effluxes at Station 22, indicating active respiration-driven calcite dissolution rather than inorganic precipitation. Additionally, relying on linearly interpolated mid-point porewater values can be misleading: for Station 22, the interpolated mid-point (Δ[CO3] = +15.38 umol kg-1carries broad uncertainty bounds extending well into undersaturation (down to -11.75 umol kg-1, Table 1). These mid-point averages obscure steep, non-linear micro-gradients near the sediment-water interface where localized interstitial undersaturation actively drives calcite dissolution. We will clarify this point about Station 22 in the updated manuscript.
Please add a figure that shows some clear examples in the article.
Response: See above comment.
Line 428-435: when considering down core samples, you need to consider bioturbation effects, effects of burrows etc as well; some of your specimens could be 200 years, the other thousands of years. And bottom water and pore water carbonate ion concentrations will vary seasonally, in relation to organic carbon flux to the seafloor.
Response: Thank you for pointing this out. We agree that both processes could play a role in our data, though we don’t think either impacts our conclusions. The fact that we have specimens at different depths from the same core showing different dissolution patterns suggests bioturbation isn’t a big deal in that core. We will add a sentence mentioning each as a possibility.
Lines 487-489: please rephrase this. You seem to have different threshold values to the two species, so it will likely be different for other species as well. Plus you cannot be sure that the relationship will be the same in different environments (for example methane seeps).
Response: We thank the reviewer for the opportunity to clarify this key distinction:
- Structural Preservation Threshold vs. Saturation Horizon: The value of nCTDX% = 15 is a physical boundary that indicates whether a test has undergone significant diagenetic alteration (partial dissolution or secondary overgrowth). It is not a geochemical threshold for the onset of dissolution, which can vary by species due to shell chemistry, nor is it an indicator for the depositional environment crossing a specific geochemical threshold
- Universal Application: Because nCTDX% = 15 simply detects whether low-density structural degradation or secondary crystal growth is present, it functions as a universal, binary index of shell state regardless of species or environmental setting (including methane seeps).
Manscript Revision: We will rephrase Section 4.5 (Lines 487–489) to explicitly separate the universal nCTDX% = 15 physical preservation index from species-specific chemical dissolution initiation thresholds.
Lines 576-578: some words missing.
Response: Good catch. We will fix this.
Line 588 based proxies.
Response: Thanks. We’ll fix this.
Line 594-594: why do rapid sedimentation rates lead to higher remineralization rates of organic matter? Does it not depend on what the sediment is made out of?
Response: Thank you for pointing this out. Definitely. We will reword this sentence with this point in mind
Citation: https://doi.org/10.5194/egusphere-2026-3333-AC2
-
AC2: 'Reply on RC2', Thomas Weiss, 17 Sep 2026
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 153 | 54 | 27 | 234 | 38 | 27 | 16 |
- HTML: 153
- PDF: 54
- XML: 27
- Total: 234
- Supplement: 38
- BibTeX: 27
- EndNote: 16
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Summary of study
This is a generally well written study presenting microCT scans of subpolar /polar planktic foraminifera species N pachyderma (left and right coiling) (13 samples) and N. incompta (7 samples) from core-tops and sediment cores from the Nordic Seas, subpolar North Atlantic and the North Pacific.
The study builds on previous work which has used the technique of uCT on samples from sites with different Δ[CO32-] values in order to investigate post depositional changes and partial dissolution of the tests of planktic foraminifera. This study is small, but would add new, previously not published species to the knowledge base.
Samples come from a mixture of Atlantic and Pacific core tops (9 samples), where bottom water Δ[CO32-] was between ~ +45 to -13 umol/kg, and down core (to 2 cm) (5) samples. One novel feature of the study is they calculate pore water Δ[CO32-] for the downcore samples. This was always considerably (up to ~30 umol/kg) less than the bottom water, with values of ~+15 to -11 umol/kg.
CT data is presented in the form of a dissolution index, nCTDX%, based on the attenuation values of the scans. The method is based on that of Iwasaki et al. (2022, CTDX%), but modified by using fragments of a standard material (NBS19) to try to standardize where the thresholds of the scan output should be selected. There is an intrinsic problem involved in trying to assess CT scans of foraminifera in that, test wall (particularly if it is partially dissolved), sediment trapped in the test and material reprecipitated inside the test are not completely distinguishable from each other. The method of thresholding used in this index, where there is a cut off for low density material, but the remaining selected pixels are dilated slightly seems a reasonable approach
Conclusions fit generally with previous findings, that inner material of planktic foram tests is the most susceptible to dissolution; that partially dissolved / partially reprecipitated material on the inside of partially dissolved tests shows as low-density material in CT scans; and that environments of Δ[CO32-] below some threshold can be identified with this technique
The methodology seems fine and study aims seem worthwhile. There are some areas which need clarification. The ms is also a bit long for the amount of data presented, it could be made more concise. I put my comments / queries / suggestions to improve the ms below.
Core tops and down core samples
I would like more information about these cores and sites. There are very large differences between calculated Δ[CO32-] of bottom water and pore water, even from sediment shallow in the core (0.5 to 1 cm). Why is this? Is this typical for the average ocean or is it particular to these sites? Are the sites particularly high in organic matter? Do they contain abundant calcite? Are the porewaters anoxic? Is the pH of the porewaters still controlled by carbonate system chemistry, or could it be influenced by acids produced by respiration of organic matter?
What were the default values used for total phosphate and total silica? Zero? Is this likely to bias results?
Actual porewater values came from depth x and then the values were interpolated between that pore water value and bottom water for each sample depth. All the data used to calculate Δ[CO32-] – alkalinity, actual depth of pore-water data, pH– should all be in the Sup Mat.
It is stated (line 70) that usually in these kinds of studies it is the Δ[CO32-] of bottom water that is used, not pore-water and this might introduce inaccuracy. In the open ocean, this might be completely fine. It may not be a good assumption for your sites. Say why. This topic needs more discussion.
Is it concluded that Δ[CO32-] from porewaters fits better with the dissolution index than using bw values? It is never clearly stated
NBS19 standard
Say more about this standard. What is it made of? Where did it come from? Why are the particle sizes so different?
CT is of course a semi-quantitative technique, attenuation intensity of a material depends not only on the material of the sample, but its form (porosity, shape). Then there is some variation in the scanner from day to day, and different scanners no doubt give different values.
I was surprised to see that the values of repeated scans of std A shown in Fig S2 are quite so variable. But I also wonder if this is actually a meaningful number. The intensity of the background should be added here. Does it vary in the same way? I would expect that the difference between the background and the standard would be more consistent, and more useful.
The implication is ( line 111 ) that CT gives extremely variable results between scans and that previous studies, which did not use NBS19 standard, used thresholds “visually chosen” for each sample and no attempt was made to provide consistency between samples. This is not the case.
Line by line comments
Abstract
Add that dissolution index nCTDX% presented here is based on CTDX% (Iwasaki)
Add information about number of samples
Line 21 – how does the refined method add to time efficiency, where is this presented?
Line 26 – n..% correlates with Δ[CO32-], what is the correlation. Add to discussion and to Conclusion
Introduction
Add information about the sites. Why were these sites chosen for investigation, what is special about them
Line 43 – state that foram tests start to dissolve in waters undersaturated wrt calcite, this is not state of the knowledge. They start to dissolve in supersaturated waters, many references for this, some even cited later
Line 91 – state that (n)CTDX% is a dissolution index and that high values represent less dense partially dissolved material. (Usually for CT the convention is that high values mean more dense material (higher greyscale, lighter colours), so it would be good to clarify for people who might be familiar with CT but not dissolution indices.) Same goes for the figures. Add an arrow to nCTDX% axes to show which direction means better preservation
Line 105 - the problems of distinguishing between partially dissolved test, trapped sediment and newly crystallising calcite is not only described by Iwasaki et al., (2022), it is mentioned in all studies using CT of forams
Methods
Describe orientation of tests in the scanner. It appears random with some on their sides, some aperture up.
All 8 tests from one sample are scanned together?
Section 2.3 image processing (line188)
There are some unexplained initials in this section eg TMX, expand
Line 209 – all slices are used to define the background? But all slices will contain std and sample, not just background. Unclear
Line 259 - Authors state they do not want to get rid of pixels lower intensity than the air peak because it comes from beam hardening (softening). What is the advantage of including scan artefacts
Line 282 –more details are needed in Sup Mat of how you calculated Δ[CO32-], but I suppose it is meant with respect to calcite (not eg aragonite)
Results
Does the offset pore and bottom water seem reasonable? Can it be explained
Line 312 - All the sample names and results should be in a results table, not just in the sup figs
Line 394 – several samples are mentioned by sample name, do they share similar sites / features?
Discussion
Line 440 - authors mention that N. incompta may be more dissolution susceptible than N. pachyderma because it has higher Mg/Ca. There are several sets of CT scans published for various species. Some from Iwasaki are plotted in Fig 7. Does the observation hold true, does N pachyderma appear have lower dissolution index than tropical species for similar Δ[CO32-] values ?
Line 451 – the reader is directed towards a large figure, need more direction as what is supposed to be seen here
Line 475 – similar to above, make a fig showing what is meant
Line 485 – why should time be a factor, and how was it concluded it is not
Line 492 – high values of dissolution index n..% does not identify between dissolution and diagenetic overgrowth. Preservation should be “evaluate preservation state of the internal walls”. How is this then to be evaluated?
Section 4.6 (line 521)
This part reads like a literature review. I don’t think it adds to the ms. No geochemical data was measured on these samples so no need to speculate so much.
Conclusions
Line 586 – how reliably can you identify tests from sites where Δ[CO32-] < 0 from the index. Looking at fig 7, it is not an exact method.
Was there a better match between the dissolution index and Δ[CO32-] for the core top or the down core data?
Line 595 – states that n..% identifies post deposition precipitation on exterior of test as shown in the sem images (Fig). I do not see convincing evidence of this in the CT scans. If it is there, direct the reader to it with a figure. If by diagenetic overgrowth, it is meant the low density material inside the test which has been described and discussed in previous studies as a partial dissolution feature, then this is different to what Groeneveld 2008 shows, which is precipitation onto well preserved tests.
Table 1
Is there a mistake, CE23012?
Figures
Fig 4 could go to sup mat
Fig 5 - Adding error bars to each symbol in the legend detracts from clarity
It would be more visually pleasing to place Δ[CO32-] on the y axis and CT on the x axis
Add information to CTDX% scale on y-axis to show in which direction preservation is better or worse
Fig 6 – add arrows to guide the reader to the post mortem calcite
Could you show CT scans of the same features
Figure 7 – it is stated this data matches well with Iwasaki data. Fig 7 shows data on two different scales. How were the y axes matched up? By assuming similar Δ[CO32-] gave similar index values???
Supplement
Figure S4, S5 add information to scale bar
0 100
less dense – more dense
What is the white diamond on the scale bar?
“Average station ..DX% increases … right”
does this have some significance? Is there some difference in the stations to the right
All the results presented in S6 etc should be in a table