the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Modelling the interactive effects of viral presence and global warming on Baltic Sea ecosystem dynamics
- 1Helmholtz-Zentrum Hereon, Max-Planck-Straße 1, 21502 Geesthacht, Germany
- 2Institut of Marine Ecosystem and Fisheries Science, Universität Hamburg, Olbersweg 24, 22767 Hamburg
- These authors contributed equally to this work.
- 1Helmholtz-Zentrum Hereon, Max-Planck-Straße 1, 21502 Geesthacht, Germany
- 2Institut of Marine Ecosystem and Fisheries Science, Universität Hamburg, Olbersweg 24, 22767 Hamburg
- These authors contributed equally to this work.
Abstract. Marine viruses have been identified as key players in biogeochemical cycles and in the termination of phytoplankton blooms; however, most models of biogeochemical processes have yet to resolve viral dynamics. Here, we incorporate a viral component into a 1D ecosystem model for the Baltic Sea to explore the influence of viruses on ecosystem dynamics under current and future climatic conditions. Virus host interactions and zooplankton grazing were mechanistically described through size-based contact rates. The model demonstrated that the presence of viruses increased nutrient retention in the upper water column. This corresponded to a reduction in phytoplankton biomass, production of dead organic matter and transfer of biomass to higher trophic levels. Viral presence played a key role in deeper water layers, near the thermocline. While warming alone reversed these trends, the combination of warming and viral presence enhanced the effect of viruses. Our results illustrate that marine ecosystem models need to incorporate viral dynamics to better predict system responses to climate change.
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Shubham Krishna et al.
Status: open (until 14 Feb 2023)
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RC1: 'Comment on bg-2022-249', Anonymous Referee #1, 16 Jan 2023
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GENERAL COMMENTS
This work tackles parts of an important subject of relevance to the journal. However, it does so in such a simplistic way that the conclusions are either obvious (viruses impact plankton production) or unbelievable (results are based on a model describing only one phytoplankton type, so there is no competition between phytoplankton that are more or less impacted by their own species-specific virus and/or by the likely selection zooplankton grazing). For some reason the authors do not seem to be aware of Flynn et al. 2022, which goes into various of the matters considered here and shows the critical importance of using a multi-species model. Here, the authors have actually used a 2-phytoplankton variant of their approach, but this is mentioned rather in passing in Discussion. If the whole work had been conducted using that more complex model then the work would have been on a much firmer grounding.
DETAILED COMMENTS
L12 Virus-host dynamics are highly specific; the specificity of this interaction here needs to be made very clear in the abstract.
L16 How did this warming interaction come about?
L22 Is there a specific reason for not referencing Flynn et al. 2022 - it seems to have rather a lot in common with this submission.
L26 Such an increase in primary production is not assured, and depends on the timing of events; these are matters for which models can help.
L28 It is very important to indicate early on that virus induced mortality is very different to that induced by zooplankton.
L69 It is very important to make it clear how many phytoplankton-virus couples are considered here - from what I can see there is just the one, implying that the Baltic has only one phytoplankton species with its virus and zooplankton. That is surely too much of a simplification. When a virus attacks its host, we must expect other phytoplankton to come to dominance. Whether they are suitable prey for the zooplankton is another important matter.
L83 Cell size is affected by factors other than temperature, and certainly the species composition (and thence the specificity of any virus attacks) will be affected during successions.
L134 I really do not see how such runs can possibly be related to reality. What happens depends as much on how uninfected species behave as it depends on that of virus-affected species.
L153 Most of what is released when phytoplankton burst would contribute to the DOM pool (as per L203), not to detritus. This does not appear to have been modelled, and neither is the activity of bacteria (and their grazers) that would be stimulated by such an event.
L213 Virus presence alone cannot lead to a regeneration of nutrients (by which I assume you mean inorganic nutrient). I do not see how, at least in the system modelled, virus attack could ever promote primary production. Can it?
L220 This model really cannot support such a claim; to do so it needs to describe the biodiversity of the plankton, and the allied specificity of viruses on components of the community.
L231 What does this 'interact actively' term mean? Viruses cannot do anything alone; they reply on the success of their host, and thence on many factors. This statement seems rather exaggerated.
L246 While this paragraph is interesting, and begs additional questions, I fear that the model is far too simple to make generalised claims like this.
L261 How was the zooplankton configured to handle this additional prey item?
L268 This is incorrect. They only impact their specific host, and the ramifications from the different host-virus interactions with competition appears (from Flynn et al. 2022) to be complex and profound.
Fig.1 That this is operated within a 1D scenario based on a real hydrodynamic scenario makes it no more representative than models operated in theoretical scenarios. The problem here is that the trophic setup is far, far, too simplistic. Viruses would only impact their own host; the idea that all phytoplankton would be impacted simultaneously in nature is not plausible. There is no bacterial activity simulated here (with or without their own viruses). Excretion of DIN by phytoplankton? What types of zooplankton are these (I assume from the 'sloppy feeding' term they are metazoan?).
Fig.5 These 'future' plots carry even more caveats than does the control. All of these appears rather too much like a ‘first try’ rather than a comprehensive attempt to explore the dynamics.
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RC2: 'Comment on bg-2022-249', Anonymous Referee #2, 23 Jan 2023
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Review of “modeling the interactive effects of viral presence and global warming on Baltic Sea ecosystem dynamics”
Summary
A 1D ecosystem model parameterized for the Baltic Sea is used to assess impacts of viral infection on biogeochemical processes (primary productivity, carbon export). A set of experiments are performed, with and without a combination of viruses and warming conditions. The study finds an interactive effect of warming and temperature on primary productivity, and carbon export.
Main comments
The study is generally clearly written, and the results are novel and interesting. The findings have clear implications for our understanding of viral impacts on ocean biogeochemistry in a future ocean. I did find a few areas where results were presented confusingly. There are also some formatting issues that may need to be addressed, and one minor query about model structure. These are all outlined below.
Specific comments
General comment: the manuscript says ‘code available on request’. It would be nice to make this available in such a way that others might be able to reproduce the findings.
Page 2 line 50: “to our best knowledge…” a recent study assessed viral impacts on ocean biogeochemistry in a 1D setting at two ocean sites (Xie and Zhang 2022). I recommend including this citation and outlining how the present study differs.
Page 6, equation 19: it looks like this is linear w.r.t. P? So, equivalent to Holling I, aka mass action? This implies the rate of grazing is unbounded, such that at very high P concentration, it can become quite large. It’s a little unusual not to bound the rate of grazing with Holling II, Michaelis-Menten, or similar (e.g. Gentleman et al. 2003). Would be nice to see if including this makes a big difference to the results.
Page 7 line 159-161: “…qualitatively matches…” I’m fine with this sort of qualitative comparison, but am I right in saying that for me to evaluate the consistency, I need to access Hjerne et al. 2019, and determine which of their data is being referred to? This seems like a heavy lift, and I suspect most readers will not make the effort. Can these data be recreated here, as you have with the Mojica 2016 data (Figure S7).
Page 7 line 166: “The maximum mortality…shorter than that caused by grazers”. I was curious as to why this is. I couldn’t find it explained in the discussion. My apologies if I missed it. If an explanation hasn’t been provided, please consider including one.
Page 7 line 168: “(Fig S7)”. Slightly pedantic on my part, but I expect the figure numbers to appear sequentially in the manuscript. This is the first supplemental figure and it goes straight to figure S7. Where are figures S1-S6 discussed? Are these discussed in the main text? Please make sure that all supplemental figures are discussed in sequence in the main text.
Page 8 line 176-180: “depth resolved … detritus production” I don’t understand the reasoning here. What does it mean to say that “higher temperatures seems to play a bigger role than stratification”? Surely temperature is mechanistically linked with stratification? Do you mean to say that, the effect of temperature on biological rates has a stronger impact than the effect of temperature on stratification? If so, how can you conclude this? It’s not at all clear to me what is being said here.
Page 8 line 184-185: “The earlier onset …. Causes an earlier increase of virus biomass”. I can’t seem to find an explanation here or in the discussion for why this is the case. Apologies if I missed it. If an explanation isn’t included, please provide one.
Page 8 line 196: “to our best knowledge” as above, there is one study with viruses in 1D (Xie and Zhang 2022). Please cite and explain how the present study differs.
References
Gentleman, W., A. Leising, B. Frost, S. Strom, and J. Murray. 2003. Functional responses for zooplankton feeding on multiple resources: A review of assumptions and biological dynamics. Deep. Res. Part II Top. Stud. Oceanogr. 50: 2847–2875.
Xie, L., and R. Zhang. 2022. Assessment of Explicit Representation of Dynamic Viral. Viruses 14: 1–21.
Shubham Krishna et al.
Shubham Krishna et al.
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