Evaluation of the Abiotic Components of the Nutrient Balance in the Barents Sea and Its Influence on Primary Production

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

After reviewing the research article “Evaluation of the abiotic components of the nutrients balance 2 in the Barents Sea and its influence on primary production (Water 3943611), my decision is that the article needs to be minor revised before it is accepted.

My reviewed comments were given below.

Basically, this article is a big work and the interpretation is fine. However, the text is not easily to read due to the complicated nutrient calculation of different water masses. The authors should try to simplify the interpretation and make it read easily. Nutrients are not the conservative elements.

 

The format of some references is not correct. The authors should revise the format through the all text. For example

 

Page 3 and Page 10

cold currents [43 Ed. 328 Terziev 1991], and dash-dotted lines show deep Atlantic water distribution [44 Matishov et al., 329 2010].

 

This methodological approach is well-established in oceanographic literature and has been extensively applied in numerous studies [23-32, 10-12].

 

obtained from the World Ocean 176 Atlas 2023 [33] database [34].

 

Stable oxygen isotope data (δ¹⁸O) and complementary salinity measurements were sourced from public archives NASA [34-35].

 

Table 1 Note: 1 – parameter descriptions are provided in Chapter 2; 2 – equation numbers are provided in Chapter 2. 

What is the Chapter 2?

 

Figure A1. Accumulated values of primary production for Si (a), N (b) and P (c) mgC m-2. Thick 699 black lines are the boundaries.

 

Revised as Figure A1. Accumulated values of primary production for (a) Si, (b) N and (c) P mgC m-2. Thick 699 black lines are the boundaries.

 

Figure A2. The values for the nutrients consumption of (%). (a) and (b) 𝑃𝐶𝑃 𝑎𝑛𝑑 𝑃𝑇𝑃 respectively; 702 (c) and (d) 𝑃𝐶𝑁 𝑎𝑛𝑑 𝑃𝑇𝑁 respectively; (d) and (f) 𝑃𝐶𝑆𝑖 𝑎𝑛𝑑 𝑃𝑇𝑆𝑖 с respectively (Eq. 2-3). Thick black 703 lines are the boundaries of the clusters (For September)

 

Revised as

Figure A2. The values for the nutrients consumption of (%). (a)𝑃𝐶𝑃, (b) 𝑃𝑇𝑃, (c) 𝑃𝐶𝑁, (d) 𝑃𝑇𝑁, (e) 𝑃𝐶𝑆𝑖 𝑎𝑛𝑑 (f) 𝑃𝑇𝑆𝑖, respectively.

Author Response

Reviewer 1

Comments 1: After reviewing the research article “Evaluation of the abiotic components of the nutrients balance 2 in the Barents Sea and its influence on primary production (Water 3943611), my decision is that the article needs to be minor revised before it is accepted.

My reviewed comments were given below.

Response 1: Thank you very much for the good rating of our article

Comments 2: Basically, this article is a big work and the interpretation is fine. However, the text is not easily to read due to the complicated nutrient calculation of different water masses. The authors should try to simplify the interpretation and make it read easily. Nutrients are not the conservative elements.

Response 2:  The "Materials and Methods" section, as well as the Supplementary Materials, have been rewritten. A figure with a calculation flowchart for primary production (Figure 1) has been added. Formulas have been added.

Nutrients are indeed not conservative. The conservative component Ccon refers to the stock of biogenic elements accumulated before the onset of photosynthesis. The article investigates the non-conservative component Cnon-con. This component (non-conservative) is equal to the difference between the conservative component (if the biogenic elements were conservative) and the measured value.

Lines 145-148. Added Figure 1 describing the calculation flowchart

Comments 3: The format of some references is not correct. The authors should revise the format through the all text. For example

Page 3 and Page 10

cold currents [43 Ed. 328 Terziev 1991], and dash-dotted lines show deep Atlantic water distribution [44 Matishov et al., 329 2010].

Response 3:  Line 419-420. Corrected. New references [42] and [43]. Thank you.

Comments 4: This methodological approach is well-established in oceanographic literature and has been extensively applied in numerous studies [23-32, 10-12].

Response 4:  Line 44,167. We did not fully understand this comment. The reference format complies with the journal's requirements: "References should be numbered in order of appearance and indicated by a numeral or numerals in square brackets—e.g., [1] or [2,3], or [4–6]". We have reordered them as [9-13, 22-31].

Comments 5: obtained from the World Ocean 176 Atlas 2023 [33] database [34].

Response 5:  Line 238. The comment is not entirely clear. The references were formatted according to the journal's guidelines. Nevertheless, they have been corrected to [32, 33].

Comments 6: Stable oxygen isotope data (δ¹⁸O) and complementary salinity measurements were sourced from public archives NASA [34-35].

Response 6:  Line 246. The comment is not entirely clear. The references were formatted according to the journal's guidelines. Nevertheless, they have been corrected to [34, 35].

Comments 7: Table 1 Note: 1 – parameter descriptions are provided in Chapter 2; 2 – equation numbers are provided in Chapter 2. 

What is the Chapter 2?

Response 7:  Line 391-392. Corrected.: «Note: 1 – parameter descriptions are provided in Chapter 2 «2. Materials and Methods»; 2 – equation numbers are provided in in Chapter 2 «2. Materials and Methods» and Appendix 1»

 

Comments 8: Figure A1. Accumulated values of primary production for Si (a), N (b) and P (c) mgC m-2. Thick 699 black lines are the boundaries. Revised as Figure A1. Accumulated values of primary production for (a) Si, (b) N and (c) P mgC m-2. Thick 699 black lines are the boundaries.

Revised as: Figure A1. Accumulated values of primary production for (a) Si, (b) N and (c) P mgC m-2. Thick 699 black lines are the boundaries.

Response 8: Line 862.  Figure A1. Accumulated values of primary production for (a) Si, (b) N and (c) P mgC m-2. Thick black lines are the boundaries. Thank you

Comments 9: Figure A2. The values for the nutrient’s consumption of (%). (a) and (b) PCP and PTP respectively; 702 (c) and (d) PCN and PTN respectively; (e) and (f) PCSi and  PTSi с respectively (Eq. 2-3). Thick black 703 lines are the boundaries of the clusters (For September)

Revised as: Figure A2. The values for the nutrient’s consumption of (%). (a) PCP, (b) PTP, (c) PCN, (d) PTN (e) PCSi ??? (f) PTSi, respectively

Response 9:  Line 864-865. Figure A2. The values for the nutrient’s consumption of (%). (a)PCP, (b) PTP, (c) PCN, (d) PTN, (e) PCSi and (f) PTSi, respectively. Thank you

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Dear Authors,

I have reviewed the manuscript “Evaluation of the abiotic components of the nutrients balance in the Barents Sea and its influence on primary production by Alexey Namyatov et al.. In this research, the effect of various abiotic factors on primary productivity such as nutrient concentration, vertical mixing, and horizontal advection was evaluated. The research seems sounds as it presents a comprehensive analysis of abiotic nutrient fluxes and their influence on primary production in the Barents Sea, offering a novel attempt to integrate δ¹⁸O-based water mass fractions with nutrient-budget modeling. Overall, the study offers an interesting conceptual approach and a rich dataset, but needs minor revisions as follows

• Line 110-112 Diatoms do not always dominate Barents Sea production; Clarify limitations of this proxy approach, especially in regions where non-siliceous taxa dominate.
• Line 110-117: The limitations and assumptions of the Arzhanova et al. should also be explained.
• Line 114-115: Clarify what validation was done, even qualitatively, or explicitly propose validation steps
• Line 250-256: The information about software tools (ODV, Statistica, Excel) is too general. Also, provide information on the statistical analysis that was performed.
• Line 136-141: Repetition of C_con makes it difficult to read and understand.
• Line 293–298: The assumption that Qₐb remains constant throughout the year within each site is questionable because of the seasonal mixing. Needs a supporting reference for your claim.
• Line 307–311: Give references for this and also explain which processes lead to the reduction of Si : C ratios and diatom decline or enhanced non-siliceous production?
• Line 427–430: This explanation should be supported by references.
• The discussion does not talk about climate-driven factors as they are also responsible for the nutrient cycle.
• The study assumes dominance by diatoms and peridinium. Include the ecological relevance of other smaller phytoplankton groups and how their omission may affect results in discussion part
• Need to provided clearer discussion of validation steps
• The conclusion does not talk about future prospective
• The supplementary figures S1-S4 to be cited in the main manuscript.

Author Response

Reviewer 2

Comments 1: Dear Authors,

I have reviewed the manuscript “Evaluation of the abiotic components of the nutrients balance in the Barents Sea and its influence on primary production by Alexey Namyatov et al.. In this research, the effect of various abiotic factors on primary productivity such as nutrient concentration, vertical mixing, and horizontal advection was evaluated. The research seems sounds as it presents a comprehensive analysis of abiotic nutrient fluxes and their influence on primary production in the Barents Sea, offering a novel attempt to integrate δ¹⁸O-based water mass fractions with nutrient-budget modeling. Overall, the study offers an interesting conceptual approach and a rich dataset, but needs minor revisions as follows

Response 1:  Thank you very much for the good appreciation of our work

Comments 2: Line 110-112 Diatoms do not always dominate Barents Sea production; Clarify limitations of this proxy approach, especially in regions where non-siliceous taxa dominate.

Response 2:  You are absolutely correct, and we acknowledge this methodological nuance. This is precisely why we explicitly state in the text: "Although this model requires further validation, we employ it here as a working hypothesis" (Line 126-129). Validating this claim is indeed associated with significant challenges and could be the subject of a separate, extensive study.

In our case, for the Barents Sea area, we consistently observed the ratio NCP_Si > NCP_N, and the inverse situation was not recorded a single time. Thus, we use the statement that NCP_Si "is used as a proxy for overall production" specifically as a working hypothesis. In the subsequent discussion, we essentially abandon the term GPP (Gross Primary Production), replacing it with production calculated from silicon (PP (NCP_Si) or from nitrogen (PP (NCP_N).

Comments 3: Line 110-117: The limitations and assumptions of the Arzhanova et al. should also be explained.

Response 3:  Added L. 109-123. New version.  Explanation and assumptions in the works Arzhanova et al. The regeneration of silicon proceeds significantly more slowly than that of nitrogen and phosphorus. Consequently, the lowest production values typically correspond to the losses of nitrogen and phosphorus in the euphotic layer, while the highest correspond to the losses of silicon. Moreover, when assessing phytoplankton production based on changes in silicon concentration, the portion of production formed through the recycling of nitrogen and phosphorus is also taken into account. Nitrates sustain primary production (new production) and are considered to facilitate the uptake of nutrients that were present at the start of the growing season or were introduced into the euphotic zone from external sources.

Summarizing the presented analysis according to the approach of N.V. Arzhanova et al., it can be concluded that production calculated from silicon (NCP_Si) reflects total production, whereas calculation based on nitrogen (NCP_N) provides an estimate of "new" production.

Comments 4: Line 114-115: Clarify what validation was done, even qualitatively, or explicitly propose validation steps

Response 4:  The verification of this methodology was comprehensively conducted and described in our previous studies. To avoid self-plagiarism, a summary of the verification results is provided in Section 2.4, "Verification of the Results Obtained," while the complete details are available in the Supplementary Materials.

Regarding the specific validation of the statement that "production calculated from silicon (NCPSi) reflects total production," we have adopted this as a working hypothesis based on the work of Arzhanova et al., and we explicitly acknowledge that it requires future empirical testing. A potential validation methodology could involve in situ marine water incubation experiments, followed by measurements of primary production, phytoplankton species composition and biomass, and the drawdown of nutrient concentrations. A critical requirement for this research is to conduct multiple experiments with phytoplankton communities of varying structure, particularly differing diatom biomass. Conducting these comprehensive bioassays with live samples will require a dedicated field season, which we plan to undertake in future work.

Comments 5: Line 250-256: The information about software tools (ODV, Statistica, Excel) is too general. Also, provide information on the statistical analysis that was performed

Response 5:  L.329-344. New version of the section.

The monthly averaged nutrient concentration data from the WOD were processed and visualized using the ODV software [37]. This software was used to interpolate the data onto a regular grid with a resolution of 10° longitude × 2° latitude. The calculation of integral (1) was also performed within ODV.

All subsequent computations, including the determination of the fa, fr, and fi ratios, nutrient uptake, and primary production rates, were carried out in Microsoft Excel.

The statistical analysis comprised the following steps:

Cluster Analysis: This was performed using the STATISTICA 7 software package [38]. The analysis incorporated 12 calculated parameters: h, , , , , , , , , , d, and . Ward's hierarchical clustering method with Euclidean distances was applied to normalized data (Ward, 1963). Ward's hierarchical clustering method with Euclidean distances was applied to normalized data (Ward, 1963). The optimal number of clusters for the k-means algorithm was determined using the Elbow method (Figure A3).

Descriptive Statistics: The mean values and standard deviations for the parameters were calculated in Microsoft Excel.

Comments 6: Line 136-141: Repetition of C_con makes it difficult to read and understand.

Response 6:  Line 178. Thank you.  Corrected

Comments 7: Line 293–298: The assumption that Qₐb remains constant throughout the year within each site is questionable because of the seasonal mixing. Needs a supporting reference for your claim.

Response 7: Yes, you are correct. The assumption that Qab remains constant throughout the year at each interpolation point is indeed one of the foundational premises of this method. Since we calculate primary production at the end of the photosynthetic period, it can be considered an annual primary production value. Within the context of an annual cycle, we can therefore refer to a mean annual Qab value at each interpolation point.

Not every statement or assumption can be directly supported by a citation. Ultimately, someone must put forward an initial premise or assertion. Assessing the seasonal variation of Qab within the annual cycle is one of the key objectives for future continuation of this work. This area of work is reflected in the section 4.3. Current Limitations and Future Directions

 Comments 8: Line 307–311: Give references for this and also explain which processes lead to the reduction of Si : C ratios and diatom decline or enhanced non-siliceous production?

Response 8:  Added L. 398-403. Such an increase in the C:Si ratio from 1.95 (according to the Redfield–Richards model) to 6.67 (based on our calculations) is likely associated with the different diatom biomasses considered in these two models. The C:Si ratio in diatoms is approximately 1 (100:93 by mass), while in dinoflagellates it is significantly higher, around 15 (100:6.6) [40, 41]. Therefore, an increase in dinoflagellate biomass naturally leads to a higher overall C:Si ratio in the community.

Comments 9: Line 427–430: This explanation should be supported by references.

Response 9:  New variant L524-530. The measured biomass ratio of dinoflagellates to diatoms was 65:35%, which does not match the calculated ratio from nutrient uptake data. This discrepancy may be explained by the significant presence of mixotrophic and heterotrophic dinoflagellates, as their nutrient uptake patterns may differ from those of purely autotrophic algae. Unfortunately, we lack data on the elemental composition of these mixotrophic and heterotrophic dinoflagellates, as well as other phytoplankton groups, which is crucial for fully understanding and modeling this inconsistency.

Comments 10: The discussion does not talk about climate-driven factors as they are also responsible for the nutrient cycle

Response 10:  Added L. 768-781. For instance, several authors have noted an intensification of Atlantification since 2007, characterized by an increased inflow of Atlantic waters. This process leads to a weakening or even a disappearance of the seasonal halocline, which enhances the upward flux of heat and nutrients from the ocean's interior. This, in turn, triggers rapid sea-ice melt and increases primary productivity [48]. Processes like this underscore the need for precise analytical tools. Addressing the mentioned limitations—by expanding the isotopic database, refining end-members, and updating the stoichiometric model—will significantly improve the method's robustness for investigating such complex ecosystem changes. Furthermore, the availability of long-term time series for salinity and nutrient data opens up opportunities to directly investigate climatic ecosystem variability, as demonstrated by the Atlantification trend. This integrated approach enables the analysis of long-term trends, tracing the pathway from changes in nutrient consumption dynamics to subsequent shifts in regional productivity, thus providing a powerful tool for understanding and predicting marine ecosystem responses to environmental change.

Comments 11: The study assumes dominance by diatoms and peridinium. Include the ecological relevance of other smaller phytoplankton groups and how their omission may affect results in discussion part.

Response 11:  A critical assumption of our model is the nutrient content of plankton, for which we used values published in 1942. Revising these stoichiometric ratios is now essential. The current methodology relies on several assumptions. A key one is that diatoms and dinoflagellates constitute 94% of the total phytoplankton biomass [16, 17]. Other taxonomic groups play a subdominant role in forming biomass peaks in the Barents Sea; their distribution is localized, and their occurrence is episodic within a season. Therefore, when averaged to an annual scale, their contribution becomes negligible.

Future work should incorporate not only diatoms and dinoflagellates but also other key phytoplankton groups to better represent contemporary marine communities.

Comments 12: Need to provided clearer discussion of validation steps

Response 12:  «2.4. Verification of the results obtained» divided into separate blocks

4.1. Verification with direct measurements of phytoplankton biomass

2.4.2. Verification with other methods for calculating primary production

Comments 13: The conclusion does not talk about future prospective

Response 13:  Added Line 814-824. The future development of this work is associated with three main directions:

Methodology refinement:

Refining stoichiometric ratios in key systematic groups (diatoms and dinoflagellates).

• Incorporating additional phytoplankton taxonomic groups into the model.
• Investigating the seasonal dynamics of abiotic factors.
• Analyzing the intra-annual variability of the nutrient regeneration coefficient.

Analysis of climatic variability: Using the available long-term time series of temperature, salinity, and nutrient concentrations, we plan to investigate the climatic variability of the components of the nutrient balance and primary production.

Expansion to other basins: A key objective is to apply this approach to other Arctic seas, primarily the Kara and Laptev Seas.

Comments 13: The supplementary figures S1-S4 to be cited

Response 13:  As referenced in the text, Figures S1 and S2 are included in the main manuscript. To maintain conciseness and comply with the journal's word count, we have moved Figures S3 and S4 to the Supplementary Materials. This also prevents undue replication of methodological descriptions already published in our previous work.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

 

The manuscript evaluating the abiotic elements of nutrient balance and the effect they have on primary production in the Barents Sea. The paper introduces an innovative combination of δ¹⁸O isotope data with nutrient data to improve estimates of primary production and points out spatial variability in the patterns of nutrient flux and their ecological significance. The detailed analysis and clusterization of nutrient inflow/outflow regimes makes significant contribution to the knowledge about biogeochemical controls through this subarctic ecosystem. The rigor of the methodology and discussion of the nutrient stoichiometry, phytoplankton community composition, and abiotic flux contributions have valuable information to provide. Nonetheless, before further consideration for publication, several questions need to be addressed to clarify and enhance the interpretation of your results:

General Comments

1. What are the implications of temporal changes in the relationships between δ¹⁸O -salinity and spatial sampling biases on nutrient flux estimates in the Barents Sea?
2. What would adding contemporary phytoplankton communities such as mixotrophs and Prymnesiophyceae do to your nutrient use/primary production estimates?
3. What are the feedbacks between new production and ecosystems changes (species changes and trophic changes) in asynchronous nutrient areas driven by nitrogen levels?

Specific Comments

Line 8: "This study builds on prior research". Mention important previous studies on the environment.

Lines 18-19: Replace "up to 68%" with "as high as 68%" for smoother reading.

Line 25: "bioproductivity" with "biological productivity" for better clarity.

Line 36: “The pelagic ecosystem is characterized by a series of water masses, each supporting a distinct biological community.” Could specify that the water masses differ in characteristics such as temperature and salinity, to clarify scientific accuracy.

Line 46-47: Needs citation support for this statement.

Lines 74-76: Define "abiotic component (𝑄ab)" earlier with more precision.

Line 94: “elucidating the synthesis pathways” rephrase into “clarifying the pathways.”

Line 95: Add brief explanation of "primary organic matter synthesis pathways."

Lines 115-116: Define "clean" production explicitly in the main text for reader clarity.

Lines 142-146: Explain abbreviations like Q_phyto, Q_rem, Ccon with a short glossary table.

Line 220: should be “δ¹⁸O” consistently, with the degree symbol in proper format check throughout the paper.

Lines 351-450: Expand briefly on dinoflagellate mixotrophy and implications for nutrient uptake patterns.

Lines 520-543: The description of the asynchronous nutrient fluxes is sound but it is advisable to include a conceptual figure to help the readers understand the nutrient fluxes better.

Lines 560-582: Discussing the effect of synchronous outflow clusters, clarify exactly how this influences primary production in relation to abiotic fluxes.

Lines 583-584: In Cluster 7, where nitrogen inflow does not influence PP, suggest speculating or citing reasons why.

Lines 585-642: Emphasize limitations in input data representativeness and stoichiometric assumptions.

Lines 623-632: The issue with low biomass season calculations is a key point; suggest highlighting this with a recommendation for future sampling and modeling corrections.

 

 

 

Author Response

Reviewer 3

Comments 1:  The manuscript evaluating the abiotic elements of nutrient balance and the effect they have on primary production in the Barents Sea. The paper introduces an innovative combination of δ¹⁸O isotope data with nutrient data to improve estimates of primary production and points out spatial variability in the patterns of nutrient flux and their ecological significance. The detailed analysis and clusterization of nutrient inflow/outflow regimes makes significant contribution to the knowledge about biogeochemical controls through this subarctic ecosystem. The rigor of the methodology and discussion of the nutrient stoichiometry, phytoplankton community composition, and abiotic flux contributions have valuable information to provide. Nonetheless, before further consideration for publication, several questions need to be addressed to clarify and enhance the interpretation of your results:

Response 1:  Thank you very much for the good assessment of our work

Comments 2: General Comments

1. What are the implications of temporal changes in the relationships between δ¹⁸O -salinity and spatial sampling biases on nutrient flux estimates in the Barents Sea?
2. What would adding contemporary phytoplankton communities such as mixotrophs and Prymnesiophyceae do to your nutrient use/primary production estimates?

What are the feedbacks between new production and ecosystems changes (species changes and trophic changes) in asynchronous nutrient areas driven by nitrogen levels?

Response 2:  These remarks are related to the PP assessment methodology.

1. On the Representativeness of Salinity and δ¹⁸O Data and the Stability of Their Relationship

The analysis utilized salinity and δ¹⁸O measurement data from various studies conducted between 1972 and 2021. Nutrient concentrations were taken from the World Ocean Atlas (WOA) as averages for the period from 1965 to 2022. Therefore, our results represent mean values over an approximately 50-year interval (from ~1970 to 2022).

The temporal variability of the relationship between salinity and δ¹⁸O in marine ecosystems, including the Barents Sea, is currently not well-studied. Nevertheless, it can be assumed that this relationship is unlikely to be subject to significant fluctuations, based on the following reasoning:

Atlantic Waters: This is the primary source governing this relationship. It is unlikely that the S/δ¹⁸O ratio in the incoming Atlantic waters exhibits substantial variation, as it is conservative and depends on the evaporation-precipitation balance along the entire path of Atlantic water mass transport.

River Runoff: Although the isotopic composition δ¹⁸O in precipitation over the vast catchment area (from Western Scandinavia to the Pechora River) can vary, its average value in the total river runoff can be considered relatively constant. This principle is used in many publications that use stable isotopes in the analysis of water masses [Supplementary materials 15-35 and others]:

Minor Influence of Other Factors: The total fraction of riverine waters in the Barents Sea, according to our estimates, is only about 1.05%. The volumes of meltwater (0.13%) and waters transformed through ice formation processes (0.05%) are also too small to significantly affect the mean S/δ¹⁸O ratio on the scale of the entire sea.

2. On the Assumption of a Two-Component Phytoplankton Composition

One of the assumptions of the applied method is that the phytoplankton community consists of two main systematic groups—diatoms and dinoflagellates. This simplification undoubtedly introduces an error into the calculations.

However, when assessing the entire Barents Sea area, the average sum of the biomasses of precisely these two groups, according to the Biological Atlas of the Barents Sea [27] (based on the analysis of 1000 samples), amounts to 94%. Thus, the contribution of other systematic groups averages no more than 6%.

The question of incorporating modern concepts of phytoplankton communities, such as mixotrophs and Prymnesiophyceae, and their impact on the assessment of nutrient utilization and primary production, is certainly relevant. However, it was not among the goals of our study and represents a separate, complex task requiring specialized investigation.

3. Conclusion

We reiterate that the discussed aspects are undoubtedly important and interesting from a scientific standpoint. Nevertheless, they fall outside the scope of the aims and tasks defined for the present study, which was focused on the abiotic component of biogeochemical cycles

Comments 3: Line 8: "This study builds on prior research". Mention important previous studies on the environment.

Response 3:  The point here is that the methodology for using stable isotopes to assess primary production has already been published by our team [16, 17]. Therefore, the present article is focused specifically on the evaluation and a more detailed description of only one component of the nutrient balance—the abiotic component.

A clarification and correction have been made to the first line of the abstract to reflect this focus.

Comments 4: Lines 18-19: Replace "up to 68%" with "as high as 68%" for smoother reading. Line 25: "bioproductivity" with "biological productivity" for better clarity.

Response 4:  Line 19. It's done. Thank you.

Comments 5: Line 36: “The pelagic ecosystem is characterized by a series of water masses, each supporting a distinct biological community.” Could specify that the water masses differ in characteristics such as temperature and salinity, to clarify scientific accuracy.

Response 5:  Lines 37-39. It's done. Thank you. Added “The water masses differ in characteristics such as temperature and salinity and other abiotic and biotic parameters.

Comments 6: Line 46-47: Needs citation support for this statement.

Response 6:  Line 47.  It's done.  Thank you. Added [8]

Comments 7: Lines 74-76: Define "abiotic component (?ab)" earlier with more precision, Line 94: “elucidating the synthesis pathways” rephrase into “clarifying the pathways.”

Response 7:  Line 78. Added (?ab), It's done. 

Comments 8: Line 95: Add brief explanation of "primary organic matter synthesis pathways."

Response 8:  Lines 99. "synthesis" removed

Comments 9: Lines 115-116: Define "clean" production explicitly in the main text for reader clarity.

Response 9:  Lines 109-129. This part of the text has been rewritten.

Comments 10: Lines 142-146: Explain abbreviations like Q_phyto, Q_rem, Ccon with a short glossary

Response 10:  According to the submission form, "Abbreviations" is located after "Conclusions"

Comments 11: Line 220: should be “δ¹⁸O” consistently, with the degree symbol in proper format check throughout the paper

Response 11:  Line 281. Replaced. Checked throughout the paper. Thank you

Comments 12: Lines 351-450: Expand briefly on dinoflagellate mixotrophy and implications for nutrient uptake patterns.

Response 12:  Lines 463-467. Added « Dinoflagellates are capable of mixotrophy, which is a combination of autotrophic (photosynthesis) and heterotrophic (consumption of organic substances) nutrition. They can switch between these modes depending on environmental conditions. Under sufficient light, they act as photosynthetic organisms, while in case of light deficiency, they readily switch to phagocytosis or osmotrophy (absorption of dissolved organic matter) »

Comments 13: Lines 520-543: The description of the asynchronous nutrient fluxes is sound but it is advisable to include a conceptual figure to help the readers understand the nutrient fluxes better

Response 13:  Lines 631-634. Figure 6 added

Comments 14: Lines 560-582: Discussing the effect of synchronous outflow clusters, clarify exactly how this influences primary production in relation to abiotic fluxes

Response 14:  Lines 675-681. By September, nutrient consumption (PT/PC%) in Clusters 5 and 2 was as follows:

• Phosphorus:45%/39% and 49%/40%
• Nitrogen:78%/69% and 71%/66%
• Silicon:33%/27% and 84%/65%

Even accounting for the abiotic outflow of nutrients from the euphotic zone, the remaining pool of nutrients—factoring in remineralization—was not fully depleted. Thus, the outflow did not limit primary production, as resources were never exhausted.

Comments 15: Lines 583-584: In Cluster 7, where nitrogen inflow does not influence PP, suggest speculating or citing reasons why.

Response 15:  Lines 596 -605. The primary factor limiting the level of primary production (PP) in this region is not the availability of nitrogen, but probably rather the year-round ice cover. A key feature of this water area is that the core of the warm Atlantic Water lies at depths of 100–200 m [34]. As a result, the surface euphotic zone is largely isolated from the mixing zone between Atlantic and Arctic Ocean waters. As noted previously, it is precisely in these mixing zones that the highest PP values are observed.

Consequently, this cluster's waters are characterized by relatively low net community production (NCP) values, which measured 30 g m⁻² by the end of September. A lower value was recorded only in Cluster 2 (26 g m⁻²). Although this assumption still needs to be studied

Comments 16: Lines 585-642: Emphasize limitations in input data representativeness and stoichiometric assumptions

Response 16:  Limitations in the representativeness of input data:

Lines 708-714. While the signatures of incoming Atlantic and Pacific waters can be reasonably derived from existing databases, characterizing riverine input in the open ocean beyond the shelf is far more complex due to the high variability caused by vast catchment areas and longitudinal dispersion. The question arises what value of δ¹⁸O should be taken as End-Members for river flow, if this value varies from 11‰ in the western Barents Sea, 20‰ in the Laptev Sea in the flow of the Lena River, and to 23-24‰ in the Bering Strait area.

Lines 737-740. A revision of the stoichiometric ratios of nutrients for phytoplankton is also necessary. The primary focus should be to refine the stoichiometric ratios for diatoms and dinoflagellates, as these groups constitute approximately 94% of the total biomass. Furthermore, it is essential to establish the stoichiometric ratios for the class Prymnesiophyceae.

Lines 741-746. While Prymnesiophyceae play a sub-dominant role in forming phytoplankton biomass peaks in the Barents Sea—being locally distributed and episodic on a seasonal scale—their impact on nutrient ratios in seawater can be traced in the aftermath of their blooms. Therefore, when considering primary production on an annual scale, the alteration of nutrient ratios induced by this class of algae remains detectable even after their peak abundance has passed

Comments 17: Lines 623-632: The issue with low biomass season calculations is a key point; suggest highlighting this with a recommendation for future sampling and modeling corrections

Response 17:  Lines 757-759. The calculation of primary production for the consumption of nutrients at low biomass at the beginning of the photosynthesis season should be singled out as a separate task.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

Authors have successfully addressed my previous comments.