the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The estimates of carbon sequestration potential in an expanding Arctic fjord affected by dark plumes of glacial meltwater (Hornsund, Svalbard)
Marlena Szeligowska
Déborah Benkort
Anna Przyborska
Mateusz Moskalik
Bernabé Moreno
Emilia Trudnowska
Katarzyna Błachowiak-Samołyk
Abstract. In polar regions, glaciers are retreating onto land, gradually widening ice-free coastal waters which are known to act as new sinks of atmospheric carbon. However, the increasing delivery of inorganic suspended particulate matter (iSPM) with meltwater might significantly impact their capacity to contribute to carbon sequestration. Here, we present an analysis of satellite, meteorological, and SPM data as well as results of the coupled physical-biogeochemical model (1D GOTM-ECOSMO-E2E-Polar) with the newly implemented iSPM group, to show its impact on the ecosystem dynamics in the warming polar fjord (Hornsund, European Arctic). Our results indicate that with a longer melt season (9 days per decade, 1979–2022), loss of sea ice cover (44 days per decade, 1982–2021) and formation of new marine habitat after the retreat of marine-terminating glaciers (around 100 km2 in 1976–2022, 38 % increase in the total area), glacial meltwater has transported increasing loads of iSPM from land (3.7 g·m−3 per decade, reconstructed for 1979–2022). The simulated light limitation induced by iSPM input delayed and decreased phytoplankton, zooplankton, and macrobenthos peak occurrence. The newly ice-free areas markedly contributed to the plankton primary and secondary production, and carbon burial in sediments (5.1, 2.0, and 0.9 GgC per year, respectively, average for 2005–2009 in the iSPM scenario). However, these values would have been higher by 5.0, 2.1 and 0.1 GgC per year, respectively, without iSPM input. Carbon burial was the least affected by iSPM (around 16 % decrease in comparison to 50 % for plankton primary and secondary production) and thus the impact of marine ice loss and enhanced land-ocean connectivity should be investigated further in the context of carbon fluxes in expanding polar fjords.
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Marlena Szeligowska et al.
Status: open (until 10 Jan 2024)
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CC1: 'Comment on bg-2023-162', Wouter van der Niet, 03 Nov 2023
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This review was prepared as part of graduate program course work at Wageningen University, and has been produced under supervision of Rúna Magnússon. The review has been posted because of its good quality, and likely usefulness to the authors and editor. This review was not solicited by the journal.
Szeligowska et al. present an interesting paper about the effect of iSPM concentration on carbon burial fluxes in newly ice free areas in fjords. They use meteorological and satellite data to make an assessment of the melting rate and dynamics in Hornsund. Most importantly a 1D coupled physical biogeochemical model including the iSPM concentration is presented. Model simulations show that the newly ice-free areas contributed significantly to primary production, secondary production and carbon burial. Plankton primary production and secondary production were halved, whereas the carbon burial had decreased with 16%. Based on the results it is rightfully concluded that iSPM concentration is an important factor in modelling carbon fluxes of newly ice free areas in arctic fjords.
Including iSPM concentration in the modelling is an innovation in the science of carbon flux modelling in polar fjords. Previous studies did not include iSPM in carbon flux modelling in polar fjords. Moreover this paper shows that iSPM concentrations are important to include in carbon flux modelling of polar fjords as it decreased the carbon burial with 16% in the model simulations. Another aspect that shows the value of this paper is that it presents a first attempt at modelling the carbon burial flux by taking into account pelagic, sympagic and benthic factors. Therefore the study provides important building blocks for expanding the modelling to a 3D high resolution model, advancing the carbon flux understanding of polar fjords. Considering this advancement, the study fits the scope of the Biogeosciences Journal.
Overall the writing is clear. Specifically, the limitations and assumptions of the 1D-approach of the model are well explained. For example, the 1D approach does not allow representation of advection and circulation in the fjord. I liked how these limitations were identified and investigated how this affects the results. Also, the effect of not including variable nutrient input in the model was discussed well. There are however a few important aspects of the writing that still need improvement. The main message of the paper and the importance of carbon burial in newly-ice free areas are weakly conveyed to the reader. I also have some major concerns regarding the validation of the model. I would like to see statistical quantification on the validation of the model. Both issues will need to be addressed sufficiently before the manuscript is accepted.
Major Comments:
- I am particularly concerned about the model validation. In the validation, reconstructed mean summertime iSPM concentrations are reconstructed based on iSPM concentration of later years and PDD AT. However, the model calculates iSPM concentration based on PDD AT aswell. So this is not independent data. Moreover, this results in only 5 data points of the 5 years. Correlation is found, but by using only 5 data points this is not robust.
Moreover, the model output of station 2 in 2006 and 2009 is assessed to be realistic (line 241) when compared to measurements of 2019. This is not convincing because they are different years and primarily because there is no statistical quantification on the accuracy of this comparison. Lastly, the spatial patterns were found to be in line with the simulation results by comparing the simulations to field measurements of 2017. There is no quantification of the statistics of this comparison either. The result of the poor validation is that it undermines the credibility of the simulation results of spatial patterns in figure 5 and the temporal patterns in figure 6.
In order to make the validation of the model more credible, I would like to see quantification and elaboration on the statistics of the comparison between (1) the model simulation of stations 4 and 5 in 2006 and 2009 and measurements of 2019 and (2) between the model simulations and field measurements of 2017 (spatial variation). More specifically, this includes a table of the R-squared and p-values of the linear regression between the model simulation of stations 4 and 5 in 2006 and 2009 and the measurements of 2019. This should be carried out for each individual date used in figure 2 of the supplement. Secondly, I would like to see at least the R-squared, p-value and coefficient of correlation of the linear regression between the model simulated iSPM concentration in all modelled stations and field measurements of iSPM concentration in 2017.
- The second major issue is that two aspects should be highlighted more in the writing. Both the main message and significance of carbon burial in newly ice-free fjords are weakly conveyed to the reader.
In line 28, 29 and 35 it is stated that the burial of carbon in newly ice-free fjord sediments is an important pathway for carbon sequestration. The importance of this pathway is not quantified however. The result is that the reader is not convinced of the relevance of this paper and its contribution to advancing the understanding of carbon fluxes and climate change. I recommend to quantify the contribution of fjords to carbon sequestration in marine sediments. For example this is done by Bianchi et al. (2020): “over the last 100,000 years, 12% of continental margin sediments have been stored in fjords, and likely have a nearly equal contribution to total marine OC burial". A quantification similar to this would suffice.
I conclude that the main message of the paper is: “iSPM input from glacial meltwater is an important factor in more accurately resolving carbon fluxes. Therefore it should be implemented in current ocean models applied to arctic fjords coastline systems.” In the abstract this is not clearly stated. It is only stated that enhanced land-ocean connectivity should be investigated further. I recommend to put the main message explicitly before this line or replace this line with a more clear sentence covering the main message.
In the conclusion the main message is there in line 510. However I suggest to change the context a bit because the two sentences before conclude that there is still a lot of uncertainties: "Considerable uncertainties remain, in particular related to the petrogenic organic carbon release". Straight after the main message, the importance of open long-term datasets is stressed (line 511-514). I suggest to move up the sentence in line 510 to right after “…. the emergence of carbon sinks due to the formation of newly ice-free areas”. This way the order is more logical for the reader and the main message is highlighted better.
- Another concern is the meteorological data that was used. Air temperature and precipitation data was used from the Polish polar station Hornsund. This station is located at the extreme west of the Hornsund fjord and at 50 kilometres distance from the eastern-most modelled stations. The meteorological conditions at the west are strongly dominated by the proximity of the relatively warm ocean. Whereas the influence of the sea decreases more inland at the east side of the study area. The meteorological data are thus not representative for the entire study area.
Considering that the air temperature is one of the two parameters used to derive the iSPM concentration in the model, having representative air temperature data is crucial for the accuracy of the model simulations. Therefore I suggest to include in the discussion chapter a statement of what the meteorological differences are in the east part of Hornsund compared to the polish polar station in the west of Hornsund. Secondly, the influence of these meteorological differences on the model simulations has to be pointed out clearly.
Minor Comments:
- A fixed carbon to Chlorphyll a ratio was used in the model. In contrast to a dynamic carbon to chlorphyll a as is explained in Yumruktepe et al. (2022). Light attenuation by chlorophyll is therefore represented slightly inaccurately in this study. This might be relevant to mention in the discussion chapter.
- The carbon burial efficiency of 70% was used, but can be highly variable in different fjords as found by Koziorowska et al., (2018). It can be useful to point this out in the discussion chapter.
- In figure 7b, the colours (red/blue) in the arrows, indicating positive and negative feedback mechanisms, are hard to distinguish.
Citation: https://doi.org/10.5194/bg-2023-162-CC1 -
RC1: 'Comment on bg-2023-162', Anonymous Referee #1, 20 Nov 2023
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The modelling study by Szeligowska et al. is an interesting study to implement iSPM into a biogeochemical-hydrodynamic carbon burial model for Arctic fjords. The authors estimate that iSPM is crucial for modelling primary and secondary production in an Arctic fjord, leading to a 50% reduction in production and reduced carbon burial. With increased runoff and glacial retreat iSPM onputs will become increasingly important with climate change, as discussed by the authors. Their overall conclusion of iSPM as a crucial compartment to modelling Arctic fjord systems is supported by a model based on in situ, metereological, and remote sensing data. The study is an important contribution showing the importance of iSPM in modelling carbon cycling in Arctic fjords.
The writing is overall clear, with a few minor grammatical issues. My main concerns lie in the model validation and discussion of the model limitations.
Major concerns:
The authors indicate a linear change of glacial discharge with climate change (e.g. L49, L374). However, this is only the case in the short term. At some point glacial discharge will decrease. On Svalbard this point seems to have been reached already (See Nowak et al., 2021 https://doi.org/10.5281/zenodo.4294063, Fig. 8).
Air temperature is a key driver for the model, yet, the data are only based on a meteorological station in the outer fjord (e.g. L109), which is quite far away from the inner bay stations. With increasing distance to the west coast I would expect a colder climate. If the authors could show a few comparisons of air temperatures in the inner and outer fjord this argument could hold, otherwise this is a major weakness that should be discussed and ideally quantified (How would colder air temperatures in the inner fjord affect the model?). Also precipitation measurements are likely different in the inner fjords and at higher altitudes and need some critical evaluation of the bias this may introduce (L114).
The validation and parametrization data are not independent (ie. Salinity is used as a proxy for iSPM, L177) as also outlined by Wouter van der Niet (Reviewer 1). In general I agree that the model validations need to be clearer and the limitations need to be discussed more critical (e.g. only 5 data points for the regression). Also the comparison of model results in different years than environmental data seem not very robust and need some statistical evaluation and more critical discussion of the limitations (e.g. quantification of interannual variability might be helpful).
The authors acknowledge subglacial upwelling as an important nutrient source (e.g. L146), yet the 1D model cannot catch the upwelling mechanism and the nutrient inputs by subglacial upwelling. The discussion justifies the lack of nutrient inflow and consumption of nutrients (especially nitrate) with low concentrations in rivers (L486), but most runoff comes from tidewater glaciers which do introduce a lot of nutrients. In other field (e.g. Meire et al., 2023) and modelling studies (Møller et al., 2023) it has been shown that this nutrient source can lead to a significant increase in primary and secondary productivity up to 10s to 100s of km from the glacier front. It seems to be a major limitation of the model that needs more in depth discussions and an estimate of how the model outputs would change if it were included (e.g. higher production without iSPM? Or would more light with less iSPM lead to a quicker nutrient depletion?).
The salinity:iSPM relationship is likely different for different catchments and for land- vs marine- terminating glaciers. This should be discussed a bit more (e.g. l178).
Specific comments:
L32: I am not sure “enhanced underwater light” fits here unless glaciers refers to ice shelves and ice tongues, which would not fit for Hornsund. With new habitats forming after glacier retreat a completely new area opens, which is likely a lot more important than light which is not just enhanced but changes from absent to present once the thick glacial ice covers disappears.
L91: How does this standard deviation compare to changes over years? Is the seasonal variability higher than interannual variability?
L95: How do you estimate the depth at the new habitats (After 2010) which is a key to this study? Did you assume the bottom depth at the glacier front in 2010 is the same in the new area once the glacier retreats? Is there any support for this assumption, or should it be mentioned as study limitation/uncertainty?
L125: How was the iSPM concentration measured? Based on water samples taken with Niskin bottles? At what depths?
L98: This sentence is confusing. Which dataset is used exactly? Currently it sounds like “a temperature dataset delivered temperature data”.
L107: Wouldn’t submarine melt be mostly affected by deeper water layers? Especially in winter, submarine melt can still be substantial in some fjords even though the SST is below 0C. If you can show CTD profiles or refer to a study with CTD profiles that show that SST is a good proxy for the overall heat at the glacier-seawater interface this argument could hold, otherwise I am skeptical.
L145: I agree that advection from outside is limited, but advection from the glacial (subglacial water) should play a role. Please differentiate.
L151: Does the 3D hydrodynamic model differentiate between surface and subglacial meltwater discharge?
L235: Why was the model period set to 2005-2009 when there is a lack of data? It seems that the other data (e.g. meteorological data) are available until 2018. Also Senintel 3 data in a higher resolution would be available since 2016. This needs clarification.
L336: Why is silicate limitation considered, but not nitrate limitation? The model has flagellates as a separate phytoplankton group, which is not dependent on silicate.
L342: Hornsund is also a West Spitsbergen fjord. Thus, I suggest writing: .. in “other” West Spitsbergen fjords (…
L351f: I don’t see how the findings of increasing PDD and melt season length in Hornsund can be important for predictions in other regions with higher temperatures? Does it mean that the finding of higher temperatures (=increased PDD and melting season length) leading to melting should be applied to other systems? This needs clarification.
L361f: This statement needs a reference.
L368: This iSPM increase mentioned based on in situ data right? I suggest clarifying it.
L395f: I suggest going into more details in the comparison of the model outputs with field studies. How does it compare to turbid vs clear fjord systems?
L398f: I don't agree with this argument. Phytoplankton blooms start when sea ice breaks up, by then sea ice algae are simply substrate limited. When sea ice is stable Phytoplankton usually does not compete for nutrients under the ice because they have too little light. If the authors disagree with me I would like to see a reference to a study that shows phytoplankton competing for nutrients with sea ice algae.
L406: What is this expectation based on?
L416: This is too speculative. If you can find a supporting reference it might still be ok to include, but I dont see that your study shows this decreased food web complexity.
L432: What are these anticipated negative effects? So far we mostly see an increase in NPP with decreasing sea ice.
L435: here might be a good place to mention the limitaitons of the model in more detail (ie. Modelling of nutrients).
L488: I do not agree. You mention that nutrients in meltwater and rivers are low, but then also that most glaciers in Hornsund are marine terminating, where subglacial upwelling is a key nutrient source increasing NPP substantially. Also the iSPM to Sal relationship would be very different in a marine terminating vs land terminating systems.
Grammatical suggestions:
Line 17: Formation of “a” new marine habitat OR Formation of new marine “habitats”
L62: I suggest using “best” instead of “most”
L65: with “a” newly implemented iSPM group.
L255: multiplied “with” the average
L289: allowed “a” coarse reconstruction
L354: “where” mass loss cannot be…
L494: “field” measurements
Citation: https://doi.org/10.5194/bg-2023-162-RC1
Marlena Szeligowska et al.
Marlena Szeligowska et al.
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