Trophic amplification of Southern Ocean plankton emerges from changing seasonality

Xue, Tianfei; Arteaga, Lionel A.; Pahlow, Markus; Frenger, Ivy

doi:10.5194/egusphere-2026-3722

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https://doi.org/10.5194/egusphere-2026-3722

Preprints

27 Jul 2026

| 27 Jul 2026

Status: this preprint is open for discussion and under review for Biogeosciences (BG).

Trophic amplification of Southern Ocean plankton emerges from changing seasonality

Tianfei Xue, Lionel A. Arteaga, Markus Pahlow, and Ivy Frenger

Abstract. Understanding how climate change will alter plankton dynamics in the Southern Ocean, a region of globally significant biogeochemical influence and strong seasonal variability, is critical for projecting the future of ocean ecosystems. Using a multi-model ensemble of 12 earth system models under the SSP5-8.5 climate-change scenario, we show that the seemingly stable Southern Ocean-wide plankton biomass masks opposing trends across three distinct biogeochemical zones. Plankton in the subpolar zone (40° S–60° S) remains near-stable owing to compensatory changes in bottom-up and top-down processes. In the subtropical zone (30° S–40° S) and seasonal ice zone (60° S–90° S), zooplankton decline and increase proportionally more than phytoplankton, constituting negative and positive trophic amplification, respectively. This trophic amplification is not uniformly distributed throughout the year but arises primarily from austral spring and summer. In the subtropical zone, shoaling-induced nutrient limitation reduces phytoplankton growth and concentration, causing a disproportionate decline in zooplankton grazing and biomass. In the seasonal ice zone, improved light availability from mixed-layer shoaling, sea-ice retreat, and warming enhance phytoplankton growth and surface concentration, driving disproportionately enhanced zooplankton grazing and biomass. In both zones, the seasonal trophic amplification signal is substantially stronger during the ecologically important spring and summer seasons than over the annual-mean, with potentially severe ecological consequences. Our results demonstrate that annual-mean projections could systematically underestimate both the magnitude and ecological severity of trophic amplification, and highlight the need for assessing seasonal and regional variations in plankton dynamics to better constrain future projections of Southern Ocean ecosystems.

Received: 24 Jun 2026 – Discussion started: 27 Jul 2026

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

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Tianfei Xue, Lionel A. Arteaga, Markus Pahlow, and Ivy Frenger

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RC1:
'Comment on egusphere-2026-3722', Anonymous Referee #1, 31 Aug 2026 reply
Does the paper address relevant scientific questions within the scope of BG? Yes

Does the paper present novel concepts, ideas, tools, or data? Yes

Are substantial conclusions reached? The conclusions are important, but could be better substantiated.

Are the scientific methods and assumptions valid and clearly outlined? Yes

Are the results sufficient to support the interpretations and conclusions? No, more support would strengthen their argument/interpretation.

Is the description of experiments and calculations sufficiently complete and precise to allow their reproduction by fellow scientists (traceability of results)? Not quite.

Do the authors give proper credit to related work and clearly indicate their own new/original contribution? They could cite some additional related work.

Does the title clearly reflect the contents of the paper? Yes

Does the abstract provide a concise and complete summary? Yes. However, L9-11 do not explain how that causes disproportionate response in zooplankton. And L12-13 are redundant with L7, suggest removing L7.

Is the overall presentation well structured and clear? Yes

Is the language fluent and precise? Yes

Are mathematical formulae, symbols, abbreviations, and units correctly defined and used? Yes

Should any parts of the paper (text, formulae, figures, tables) be clarified, reduced, combined, or eliminated? Yes

Are the number and quality of references appropriate? Yes

Is the amount and quality of supplementary material appropriate? Yes

General comments
This paper assesses projected changes in phytoplankton and zooplankton in three regions of the Southern Ocean as simulated by an ensemble of Earth system models (ESMs) under SSP5-8.5. The study finds three different patterns in the three regions, with trophic amplification in two of them. A new contribution of this study is examining if there is seasonal trophic amplification, instead of just a difference between a future time period (e.g. 10-30 yr mean) and the contemporary time period. The study also attempts to attribute the changes using a budget analysis for both phytoplankton and zooplankton. Though the results are supported by evidence, not all the interpretations of the results are substantiated. The key message is important and clearly described, highlighting seasonal changes and how they could be obscured by only examining annual means. It also prompts next steps for assessing downstream impacts of the seasonal trophic amplification.
The Results and Discussion often hypothesize how temperature, light, and nutrient availability caused the changes in plankton biomass, concentrations, and rates (e.g. L197, L280, L326). However, these terms are readily available from the ESMs on the ESGF server. A seasonal analysis of temperature, sea ice, downwelling radiation, light limitation, N limitation, and Fe limitation akin to the MLD analysis in Figures 4-6 would greatly strengthen the paper by attributing the mechanisms rather than hypothesizing on them.
The Arteaga et al. 2020 reference is not adequate for these statements because it examined Argo observational data, not model output.

Section 3.2.3 head reads “Spring and summer light availability drives positive trophic amplification in the SIZ,” but light availability is not directly examined.

Specific comments
Additional references
L24: Add also Petrik et al. 2020, Guibourd de Luzinais et al. 2023.

L34: Add also Asch 2015, Chen et al. 2025.

L56: Suggest adding Kearney et al. 2021 that has a detailed description of the BCG model components.

Methods need more detail
L53: Please list all the variables you used for this analysis and their CMOR names too.

Section 2.1: Add definition of years for "contemporary" and "future" analyses.

Table 2: Which years?

L144-147: I do not fully understand these methods. i) I don't understand why the normalization step is needed. ii) Is there only one budget per term (P, Z) from the multimodel mean, not one budget per term per model? iii) Seems like the averaging could lead to a mismatch of loss/gain terms, which then would be absorbed by the Other term.

Not clear where many of the numbers in the Results section come from
L206-207: How is the 67% more calculated? 10%/6%?

L233: 30% looks closer to 20%.

L252: Is 50% stronger the comparison between 16% vs. 10%?

L313-314: How is the >4x quantified? The relative change in Fig 6 c and d looks like 70% vs. 35% (~2x). Is it referring only to the Jan diff that is ~4x?

L317: “eleven times as much” Can you please give the two numbers for phytoplankton and zooplankton for verification of this quantity?

Imprecise language
L112-113: “Not capture fully” is imprecise wording. These could be captured, but ESM modelers choose not to. Omnivory occurs when >1 zooplankton type, which is represented in your ensemble. Slower turnover rates can be accomplished with differential temperature-dependence, mortality, and/or representation of life history stages.

L270: Is a deltaT of <0.3 mmolC/m2/d sharp? What is the context or criteria for calling this sharp?

L285: The MLD difference looks biggest to me (from the two lines) in Jul-Sep, but the bars are the smallest then.

L292: The statement “increasing loss terms offset the higher grazing intake across all seasons” is not accurate. Losses < Grazing Jun-Oct.

L295: You say there is no amplification window, but It seems that S, O, and D meet the criteria.

L322: “throughout most of the year” Just Aug-Jan, that's half not most.

L329: Elevated grazing only compensates Aug-Jan.

L330: “increase in zooplankton biomass” Losses seem to exceed grazing in Fig 6f (negative deltaT), but the change in biomass is positive Feb-May.

L401: “different … directions” All the shifts look earlier to me in Supp Fig C3.

L94-95: Could the difference between Argo and BGC-Argo be the time range? e.g. Argo has 10 years under cooler conditions and is missing 3 warmer years?

L165-166: I understand this in theory, but the figures do not meet my expectations given these explanations. e.g. Fig 4d,f: deltaZ is positive Jan-Jul, suggesting the difference between 2000s and 2090s is decreasing those months, but the relative change in those months is very large.

L196: Could the stability simply be that phytoplankton biomass has decreased proportionally with PP and GRAZ, such that u 🟰 PP/phy and g 🟰 GRAZ/phy are the same?

L248: October is also the biggest decrease in MLD in future compared to contemporary.

L260: I think this should say “decreasing grazing mortality.” dGrazing is lower Oct-Jun as indicated by the bars. dGrazing is negative in the amplified period, both in the budget (Fig 4c) and Dec-Apr in the g/g2000s comparison (Fig 4b), so it must be the decreased growth in (Fig 4b) that resulted in reduced PP.

Section 3.2.2: Could also mention that both phytoplankton and zooplankton show phenological shift earlier.

L285-286: How does one see that “From August to October, enhanced phytoplankton production driven by mixed-layer shoaling induced light improvement and rising temperatures leads to a subtle increase in phytoplankton biomass” in 5e? It does not show MLD or light. And deltaT is positive for May-Sep, but very negative for Oct.

L304: Could also mention a phenological shift earlier for both phytoplankton and zooplankton.

L327: Grazing can also be enhanced by warming. This goes for all regions.

Supp Fig B3: Point to your Supp figure with surface concentrations anytime you mention enhanced concentrations rather than integrated biomass in Results.

Results: How is surface irradiance projected to change in these 3 regions? Other studies (e.g. Krumhardt et al. 2022) have shown that some get cloudier and others less cloudy?

L350-353: You say your results emphasize the ZPC mechanism as if the other two were not important components of your results, but you didn’t assess ZGE or ZTL. Also, ZPC is GRAZ/PP right? Might be good to show in your 3 regions historically and over time. Especially since the ZGE, ZTL, and ZPC changes were quite variable around the S Ocean in the GFDL model.

L359: You can see if this is true of the heterotrophic processes by checking the temperature-dependence terms in each BGC model. Some examples in Kearney et al. 2021.

L360-361: Could you explain this “partially counteracted amplification” more? Are you only considering increased grazing with increased temperature (not increased metabolic demand and other losses)? e.g. Increased phytoplankton + Disproportionately higher grazing = Greater increase in zooplankton (reinforce positive amplification), whereas Decreased phytoplankton + Higher grazing = Weaker decrease in zooplankton (counteract negative amplification). This would only be true if the increased grazing on less phytoplankton biomass can meet the higher metabolic demands.

L372: It could also arise from biomass not accumulating in the zooplankton groups because their generation time is shorter than the zooplankton with complex ontogeny that actually live in this region (and thus biomass turnover rate is faster).

L377 and Fig C4: I would like a statistical test of this if possible. I notice some patterns. i) 2p2z-noFe outlier in STZ and SPZ. ii) 1p1z low range of STZ and high range of SPZ. iii) withFE lower than noFe in SPZ.

L383-384: How uncertain are the other physical changes, like sea ice, across the MME?

L400: The phenological shifts can also be seen in Figs 4-6.

Technical corrections
L29: The Asch et al. 2019 paper was specifically about fish spawning. This detail should be added.

Figure 1: Add a colorbar with units for chl. In the SIZ, the arrow is at the start of the seasonal cycle, which disagrees with the text saying, “austral spring and summer,” while the biomass is higher than the historic pattern in the last half of the cycle.

Table 2 and throughout: I’d suggest using mgC instead of mmolC for plankton biomasses, as I think plankton ecologists are more familiar with thinking in these units.

Figure 2: i) Please make this figure the whole page width and choose a different color for the purple line. It is too similar to the black. ii) I also suggest using the same y-axis limits for all left-hand phytoplankton and zooplankton, 0-180, and the same y-axis for all right-hand phytoplankton and zooplankton, 0-360. iii) Clarify if both the red and purple lines use the left y-axis labeled "obs".

L120: Can you add an estimate of how much zooplankton data is overlapping in both of these vs. how much is different? I assume <2012 is the same as COPEPOD and >2012 is new to Yang?

Eq 6: Technically, there is an efficiency constant on the GRAZ term such that not all GRAZ becomes zooplankton biomass.

Figure 4b, 5b, 6b: Add the one-to-one line to these plots. Also, how is one supposed to be able to distinguish April/Aug, Jan/June/July and Mar/May?

L273 and throughout: “predator-prey” is the common terminology, not “prey-predator.”

Figure A1: It would be nice to also see a second figure next to it that shows the # of months with data for each location.

Figure A2: Label (a)-(l) with each ESM so one does not have to go back and forth between the table and this figure to know which is which.

Figure B3: Suggest adding water column-integrated plots next to these to make comparison easier. Or add dashed lines to these.

L464/Figure B4: Just curious, why is the Fe time series so cyclical?

Figure B5: Would these changes be isolated to only the SIZ?

Figure C1: Why surface and not integrated here?

Figure C3: I do not see any blue bars. Is that correct?

References
Asch, R. G. (2015). Climate change and decadal shifts in the phenology of larval fishes in the California Current ecosystem. Proceedings of the National Academy of Sciences, 112(30), E4065-E4074.
Chen, K. S., Petrik, C. M., Asch, R. G., Thompson, A. R., & Auth, T. D. (2025). Continuing Long‐Term Shifts in Larval Fish Phenology in the Southern California Current Ecosystem Are Matched by Rapid Advances in the North. Global Change Biology, 31(3), e70141.
Guibourd de Luzinais, Vianney, Hubert Du Pontavice, Gabriel Reygondeau, Nicolas Barrier, Julia L. Blanchard, Virginie Bornarel, Matthias Büchner et al. "Trophic amplification: A model intercomparison of climate driven changes in marine food webs." PLoS One 18, no. 8 (2023): e0287570.
Kearney, K. A., Bograd, S. J., Drenkard, E., Gomez, F. A., Haltuch, M., Hermann, A. J., ... & Woodworth-Jefcoats, P. A. (2021). Using global-scale Earth system models for regional fisheries applications. Frontiers in Marine Science, 8, 622206.
Krumhardt, K. M., Long, M. C., Sylvester, Z. T., & Petrik, C. M. (2022). Climate drivers of Southern Ocean phytoplankton community composition and potential impacts on higher trophic levels. Frontiers in Marine Science, 9, 916140.
Petrik, C. M., Stock, C. A., Andersen, K. H., van Denderen, P. D., & Watson, J. R. (2020). Large pelagic fish are most sensitive to climate change despite pelagification of ocean food webs. Frontiers in Marine Science, 7, 588482.

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Citation: https://doi.org/10.5194/egusphere-2026-3722-RC1
RC2:
'Comment on egusphere-2026-3722', Anonymous Referee #2, 24 Sep 2026 reply
Does the paper address relevant scientific questions within the scope of BG? Yes

Does the paper present novel concepts, ideas, tools, or data? Yes

Are substantial conclusions reached? Yes

Are the scientific methods and assumptions valid and clearly outlined? Partly

Are the results sufficient to support the interpretations and conclusions? Partly

Is the description of experiments and calculations sufficiently complete and precise to allow their reproduction by fellow scientists (traceability of results)? Partly

Do the authors give proper credit to related work and clearly indicate their own new/original contribution? Yes

Does the title clearly reflect the contents of the paper? Yes

Does the abstract provide a concise and complete summary? Yes

Is the overall presentation well structured and clear? Partly

Is the language fluent and precise? Yes

Are mathematical formulae, symbols, abbreviations, and units correctly defined and used? Partly

Should any parts of the paper (text, formulae, figures, tables) be clarified, reduced, combined, or eliminated? Yes

Are the number and quality of references appropriate? Yes

Is the amount and quality of supplementary material appropriate? Yes

The manuscript “Trophic amplification of Southern Ocean plankton emerges from changing seasonality” by Tianfei Xue et al. investigates plankton trophic amplification in the Southern Ocean until the end of this century under SSP5-8.5. Trophic amplification is prevalent in the subtropical zone and the sea-ice zone, but with opposite patterns. This study highlights the importance of seasonal research, as some phenomena are concentrated in specific periods. However, some analyses and interpretations of the mechanisms of Southern Ocean trophic amplification in this manuscript lack scientific logic and evidence. I will list some points that I am concerned about, which will enhance confidence in this manuscript if you can address most of them.
Major comments:
The manuscript uses the multi-model mean throughout to compare changes in phytoplankton and zooplankton biomass, as well as variables used to interpret relative mechanisms such as growth rate and grazing, in long-term time series or seasonality. This might be inaccurate when using only themulti-model mean. Assuming that the amplification rate is 200% (i.e., phytoplankton increase 10% and zooplankton increase 20%) for the multi-model mean, one or two models may behave with extremely strong trophic amplification, e.g. 500%, which counteracts the amplification rate of other models. It is practical to discover how each model behave I suggest comparing trophic amplification across the twelve models, with the figures or tables presented in the appendix. If most models (at least 10) show strong, clear trophic amplification, that will give confidence to support this. Otherwise, if only about half of the models show this phenomenon, it means trophic amplification appears only in some models through specific processes in the simulation. You then might need to analyse the processes and mechanisms among models.

In the phytoplankton and zooplankton tendencies, you describe the phytoplankton grazing loss as beingthe same as the zooplankton grazing gain. However, this is wrong and highly biased. The “graz” variable in CMIP6 output represents the grazing flux and therefore describes phytoplankton grazing loss. However, zooplankton grazing gain is often the assimilation part of the total grazing flux, where the assimilation rate ε is a parameter in biogeochemical models. Equation 6 should therefore change to Tzoo = dzoo/dt = εGRAZ − Please review the model description document for all 12 models, identify their relative descriptions and equations, and update the zooplankton gain/loss processes and fluxes. This will help improve the accuracy of the zooplankton gain/loss processes and fluxes.

Some factors, such as nutrient limitation and light exposure, are mentioned to explain changes in phytoplankton biomass (e.g., L197, L264, and L280). However, no evidence (e.g. figures or tables) is provided in this manuscript to prove their relationship. You should download nutrient outputs (e.g., nitrate, silicon for diatoms, and dissolved iron) or limitation terms, as well as the light field, from ESGF. The data include surface and in-depth fields, which can be compared with surface plankton biomass and integrated biomass, respectively. This will help interpret the contribution of environmental variables to changes in plankton biomass under future climate change.

Minor comments:
Figure 1: It wouldbe good to have a colour bar with the three different shadings. It is hard to distinguish chlorophyll concentration among zones. Label the three zones with three colours in panel (b), for example, beside the panel.

L61: There is an appropriate reference to be cited here: Cheng, M., Maher, N., and Ellwood, M. J.: Evaluating the performance of CMIP6 models in simulating Southern Ocean biogeochemistry, Biogeosciences, 22, 7269–7291, https://doi.org/10.5194/bg-22-7269-2025, 2025.

Figure 3: It should be checked and stated here whether the error bars and boxes in panels (a, c, e) denote the errors calculated by the mean for each model or all data points for each model.

L149-150: It's not appropriate to say “cannot fully close the budgets”as you have already introduced Ophy and Ozoo. Change "fully close" to "explicitly resolve all terms in".

L184-185: See comments on Fig. 3. If the error bars and boxes in Fig. 3a, c & e are calculated among all data points for all models but not region means for all models, this sentence is not right. If the error bars are calculated from all data points across all models, these panels can better show larger spatial variation rather than MME spreads of plankton biomass.

L196-197: Increasing temperature greatly enhances primary production and phytoplankton growthrate in STZ in CMIP6 models, counteracting a great part of the nutrient limitation effect by mixed layer shoaling (Cheng et al., 2026).

L198-200: The stability of the grazing rate in half the models that include the temperature term f(T) in the zooplankton grazing function could be explained by the balance of higher temperature and decreasing phytoplankton biomass. However, the other half of the models do not include f(T) in their grazing function. If phytoplankton biomass decreases in these models, the grazing rate may not remain stable; instead, it may decrease. This expression should be careful that "could be attributed to" is too strong because this statement can only be supported by half of the models. You shouldchange it to "may be partly attributed to" and carefully check the grazing rates of models without f(T) if they are decreasing.

L200-203: The logic here is unclear. You first said “the decline in phytoplankton biomass is driven by other increased loss processes or cannot be fully understood”and then said “it is primarily driven by nutrient limitation”. You said “this decline differ across season” and then said “it's concentrated in spring and summer”. It is verbose and hard to understand. You should simplify these sentences and state like, "the decline in phytoplankton is primarily driven by nutrient limitation, especially in austral spring and summer, as revealed by the seasonal analysis in Sect. 3.2.1".

L216-218: It is mentioned that there is no clear change of total phytoplankton in the SPZ. However, this stability (-1% change) is attributed to improved light conditions and stable iron conditions. No negative effect balances it. This could be caused by mixed-layer shoaling, which shoals the phytoplankton growth depth, leading to increased surface phytoplankton biomass (Fig. B3) and stable integrated biomass (Fig. 3). This should be interpreted here.

L218-219: Although NPP is projected to increase in SPZ over the century which is proved by a few studies (Cheng et al., 2026; Fisher et al., 2025; Tagliabue et al., 2025), many studies revealed that NPP has been declining over the past few decades, both by satellite and BGC-Argo product (Cheng et al., 2026; Ryan-Keogh et al., 2023; Tagliabue et al., 2025). Much of the literature presents the opposite view. This sentence should be rewritten, and the results need further interpretation. Liniger et al. (2025)report annual net community production increases across most of the Southern Ocean, which differs from the phytoplankton production observed here. You should either remove "which agrees ... 2025)" and compare it to the observational studies (satellite and BGC-Argo) I mentioned above, which provide observed NPP trend analyses.

L220-221: The wording here is too strong, e.g., "Leadingto", "and hence". You should either provide evidence to prove this relationship (shoaling mixed layer -> increased surface phytoplankton concentration -> intensified zooplankton grazing), or use precise vocabulary. Increased surface phytoplankton concentration may be mainly driven by higher sea surface temperature in the SPZ (Cheng et al., 2026).

L229-230: The causality in this sentence is too strong. Strong shoaling in MLD could increase light exposure and improve growth conditions, but it can also reduce nutrient supply andrestrain phytoplankton growth. I would suggest deleting ",partially due to ... (Fig. 3b&d)" and using a more precise relationship.

L231-233: “the shoaling mixed layer along with sea ice retreat”should be changed to “enhanced light conditions caused by the shoaling mixed layer along with sea ice retreat”. Moreover, increasing temperature also greatly enhances the production here (Cheng et al., 2026).

L254-255: "during austral spring" should be changed to "during late austral spring".

L259-261: Assuming the reduction in primary production is during austral summer here, then grazing trend is negative during this period (Fig. 4b). You should remove the statement of "a lower phytoplankton biomass as a result of increasing grazing mortality". Instead, this lower phytoplankton biomass may mainly result fromdeteriorating growth conditions. You should rephrase this sentence.

L263-264: Fig. 4b cannot support this sentence that mixed layer shoaling can result in nutrient limitation. You should make some figures to support the nutrient limitation, see the third major comment.

L264-266: Δg/g2000s - Δu/u2000s > 0 (enhanced grazing mortality outweighs the enhanced phytoplankton growth rate) does not exist during the rest of the year, but only in a few months. You should rephrase it.

Figure 4: (a) As I can see, there are two dotted lines in panels a, c, d and two lines overlap in panels a and c. However, you only describe one horizontal line in the caption. Please check whether the description is missing or if there is a plotting error. (b) Moreover, the horizontal lines in the panels seem to denote the relative change at the end of the century rather than the annual mean. Please check both the plots and the caption and ensure they match. (c) Some month abbreviations in panel b are duplicated, such as M, J, and A. You should use a more unique way to denote each month. (d) You should replot panel b to make it clearer to compare Δg/g2000s and Δu/u2000s: use the same scale of x and y axis; plot an auxiliary line (y=x). (e) These comments are also appropriate for Figs. 5 and 6.

L285-286: The cited figure should be changed from fig. 5e to fig. 5c.

L305-306: There is no evidence provided here to support the idea that MME reproduces the seasonality well. You should either provide relevant analysis or rephrase/remove the relevant description.

L307-308: Similarly, "strong light-driven seasonal cycle" is unsupported. You cannot state the strength of the light-driven seasonal cycle among zones without evidence. Please provide relevant analysis and rephrase the description accordingly.

L351: You should provide a detailed definition of ZPC, which you use throughout the discussion, to help readers better understand what you are discussing.

L353-356: The mechanism interpreted here is hard to follow. It's unclear why phytoplankton concentration, rather than integrated biomass, can control the zooplankton response. Moreover, physical forcing is raised here to drive ZPC, which is also unclear. The authors should interpret these mechanisms in more detail, rather than making such a leap.

L359: “If heterotrophic processes are more temperature-sensitive”: There is an appropriate reference to be cited here:Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., & Gehlen, M. (2015). PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies. Geoscientific Model Development, 8(8), 2465–2513. https://doi.org/10.5194/gmd-8-2465-2015. PISCES-v2 uses different temperature-sensitivity parameters for phytoplankton and zooplankton, with f(T) of 1.066^T and 1.079^T, respectively.

L370: Change “equalling” to “often exceeding”. Zooplankton biomass is higher than phytoplankton in the Southern Ocean summer (Yang et al., 2022).

L376-377: Statistical analysis should be done to prove “relative changes in phytoplankton biomass are not influenced by the structural complexity of ecosystem models” (i.e. p>0.05), see examples in Fig. 15 of Cheng et al. (2025).

L377-379: This expression makes it confusing. Assuming trophic amplification patterns are not influenced by model structural complexity, can they be simulated by simple processes and underestimated by specific parameterisation, or do they require more complex models to constrain them well? The expression of "robust to differences in model complexity" is inaccurate and exaggerated. You should reconsider this and rephrase it with a more qualified statement.

Reference
Cheng, M., Adroli, N., Maher, N., & Ellwood, M. J. (2026). A temperature-normalised view of southern ocean primary productivity under climate warming. Environmental Research Letters, 21(13), 134018. https://doi.org/10.1088/1748-9326/ae83d0
Cheng, M., Maher, N., & Ellwood, M. J. (2025). Evaluating the performance of CMIP6 models in simulating Southern Ocean biogeochemistry. Biogeosciences, 22(22), 7269–7291. https://doi.org/10.5194/bg-22-7269-2025
Fisher, B. J., Poulton, A. J., Meredith, M. P., Baldry, K., Schofield, O., & Henley, S. F. (2025). Climate-driven shifts in Southern Ocean primary producers and biogeochemistry in CMIP6 models. Biogeosciences, 22(4), 975–994. https://doi.org/10.5194/bg-22-975-2025
Liniger, G., Sharp, J. D., Takeshita, Y., & Johnson, K. S. (2025). Two Decades of Increase in Southern Ocean Net Community Production Revealed by BGC‐Argo Floats. Global Biogeochemical Cycles, 39(8). https://doi.org/10.1029/2024gb008371
Ryan-Keogh, T. J., Thomalla, S. J., Chang, N., & Moalusi, T. (2023). A new global oceanic multi-model net primary productivity data product. Earth System Science Data, 15(11), 4829–4848. https://doi.org/10.5194/essd-15-4829-2023
Tagliabue, A., Ryan‐Keogh, T., Baker, A., Bibby, T. S., Follett, C., Lohan, M. C., Naveira‐Garabato, A., Mayor, D. J., Milne, A., Moore, C. M., & Ussher, S. (2025). The Evolution of Southern Ocean Net Primary Production in a Changing Climate: Challenges and Opportunities. Global Change Biology, 31(12). https://doi.org/10.1111/gcb.70653
Yang, G., Atkinson, A., Pakhomov, E. A., Hill, S. L., & Racault, M. F. (2022). Massive circumpolar biomass of Southern Ocean zooplankton: Implications for food web structure, carbon export, and marine spatial planning. Limnology and Oceanography, 67(11), 2516–2530. https://doi.org/10.1002/lno.12219

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Citation: https://doi.org/10.5194/egusphere-2026-3722-RC2

Tianfei Xue, Lionel A. Arteaga, Markus Pahlow, and Ivy Frenger

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Short summary

Climate change alters the balance between ocean plants (phytoplankton) and the tiny animals eating them (zooplankton) in the Southern Ocean. Using 12 climate models, we show zooplankton respond more strongly to climate change than phytoplankton, but mainly in spring and summer. Near Antarctica zooplankton increase more than phytoplankton; in subtropical waters they decline more. Annual averages hide these seasonal extremes, underestimating ecological impacts on marine food webs.


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