the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Nov 2024
A Mathematical Model of Microbially-Induced Convection in Sea Ice
Abstract. Through its role as a an interface between ocean and atmosphere, sea ice is important both physically and biologically. We propose here that the resident microbial community can influence the structure of sea ice, particularly near its ocean interface, by effectively lowering the local freezing point via an osmolytic mechanism. The lower freezing point can enhance fluid flow, linking a bottom, convective ice layer with the underlying ocean, resulting in improved nutrient uptake and byproduct removal. A mathematical model based on a previously suggested abiotic one dimensional simplification of mushy ice fluid dynamics is used to illustrate, and supporting measurements of freezing point depression by lab grown sea ice-associated organisms are provided.
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RC1: 'Comment on egusphere-2024-2696', Anonymous Referee #1, 17 Apr 2025
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Cryosphere Review - A Mathematical Model of Microbially-Induced Convection in Sea Ice
Overall Summary/Review – General Comments
The manuscript A Mathematical Model of Microbially-Induced Convection in Sea Ice by Kraitzman et al. describes a combined laboratory and modeling effort to characterize and simulate the impacts of biological dynamics – and particularly the influence of biologically produced antifreeze compounds – on the thermophysical and chemical evolution of sea ice. This is an interesting and valuable new addition to the field of sea ice modeling that explores the coupled feedback between sea ice properties (temperature, salinity, porosity), osmolyte production by sea ice biological communities, and the evolution of the ice layer. While the model is relatively generalized and presents a basic ‘effective salinity’ role for the osmolyte’s impact on the ice via the alteration of the liquidus, it provides a foundational step to build additional complexity upon and already sheds light on potential dynamic feedback between resident sea ice organisms and their environment. I believe there are some key clarifications that should be made by the authors in both the laboratory experiment description as well as the modelling section to aid in the comprehension and accuracy of their results and conclusions – I outline these in the ‘Specific Comments’ section below. Additionally, I believe there could be a more explicit discussion of the implications of the investigation’s results – moving beyond generalized statements of importance/warranting future attention toward isolating how specific simulated dynamics (e.g., cyclic convection induced by microbes) could influence broader Earth systems (e.g., nutrient/salt flux into the ocean and the impact on ocean circulation or biological production in the water column). I feel that such targeted discussion could amplify the impact of the paper by providing readers with tangible examples of how this type of modeling work can be helpful for the broader scientific community.
Specific Comments
- In the Introduction – While the addition of the biological antifreeze component to a sea ice model is novel, there is a general lack of discussion of previous modeling work that has been done exploring other biogeochemical processes (which is akin to and relevant to this publication, as these processes go hand in hand – e.g., nitrogen, carbon, iron, silica cycling, growth/death rates of resident in-ice biological populations). This is a new and dynamic field, and much work has been done in the past 12 years since the Vancoppenolle et al., 2013 paper cited at the end of the introduction. I think including some additional background on the current state of biogeochemical processes modelling in sea ice is likely warranted.
- The experimental component of the paper attributes the additional ~1°C of freezing point depression (below that of the seawater samples) to the presence of osmolytes in the system. However, there are no experimental results to show that this additional freezing point depression (e.g., that seen in Figure 2) could not be attributed to the f/2 media contained in the biological and supernatant samples. f/2 media contains a range of sodium salts that would be present in both samples, and as such could be the cause of the additional freezing point depression if the concentrations are non-negligible. I think it would be valuable to demonstrate that the seawater + f/2 media in the absence of cells/osmolytes cannot produce the observed signal, either experimentally or theoretically (by quantifying the level of sodium salts in the samples and ensuring they cannot impact the freezing point by 1°C).
- The authors state “In the second case, there is the possibility of transient occupation in which microbes from an ocean reservoir only pass through the ice without any significant residence time, so we also consider growth and decay processes. In the sessile case, though, transience is not an issue so for simplicity we do not include growth/decay in the microbial model.” I do not understand why growth and decay would not be relevant to the sessile case. I would imagine growth and decay would be more important, given no new organisms can be advected into the system like in the planktonic case. The impacts of salinity and nutrient concentration would likely be critical to these sessile organisms that rely on the upwelling of seawater to replenish nutrient stores and/or maintain a non-toxic level of salinity. Further explanation for why this choice was made in the model is warranted. I think it could be incredibly interesting to see the link between nutrient availability, osmolyte production, and the convective regimes.
- I think a plot of porosity evolution for the simulations should definitely be included in the manuscript. This is a critical factor governing the fluid flow throughout the system and is a property that is tied directly to the microbial dynamics explored in the investigation. An accompanying discussion of the feedback between salinity/osmolyte concentration, porosity, temperature, and biological activity (and associated observable features in the model results) could also help describe the system to non-experts who don’t necessarily think about the interdependent nature of these systems.
- There is an initial spike of osmolytes in the upper reaches of the ice in both simulations due to the initiation of the model – what conditions cause this spike (particularly near around 20cm below the ice-atmosphere surface)? Additionally, these high concentrations seem to then diffuse away – what causes this reduction in osmolyte concentration after the initial spike if the permeability of these upper reaches is quite low so as to not allow fluid flow or osmolyte diffusion?
- The authors say that the decrease in temperature above the convective layer in the sessile simulations are related to a reduction in thermal conductivity associated with increased brine volume “temperature above the convective layer actually decreases with introduction of biofilm activity. This seems to be a consequence of an increase in brine volume fraction there due to osmolyte production, which results in a drop in thermal conductivity”. Is this not just purely a consequence of the defined liquidus relationship – i.e., osmolyte concentration increases, local thermodynamic equilibrium is assumed, and therefore the temperature of the system is required to decrease?
- The authors state “Note also the slow build up of osmolyte in a layer near the top of the convective region, Fig. 3 middle left, where convection is slow due to low ice permeability; this layer eventually discharges as well (not shown).” But do not expound on this further. I think this is an interesting result that could have some substantial implications – deep convection that exceeds the more continually convecting layer near the ice-ocean interface could provide substantial (and apparently punctuated) fluxes of material (salts, organics, etc.) to the underlying ocean that could impact ocean dynamics and biological productivity. I think it could be worth discussing this further, if only hypothetically.
- Digging into the numerical methods section of Appendix B here. Steps 1-3 state that equations A12, A11, and A10 are solved using the bulk fields. Are these equations solved iteratively? They appear interdependent, such that solving for temperature, will impact the porosity, which will impact salinity and osmolyte concentration - BUT this will in turn impact temperature again via the liquidus (equation A7). I believe these will ultimately converge/stabilize to any desired tolerance if iterated (and perhaps this is already being done, in that case this comment can be ignored and I would just mention this is being done in the text), but if it isn’t being iterated the choice of timestep could impact the results – it may not if the timestep is sufficiently small – but given this is the thermodynamic equilibrium assumption that governs the phase, temperature, and salinity of the system the authors may want to check if this is impacting the results.
Citation: https://doi.org/10.5194/egusphere-2024-2696-RC1
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