the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Nov 2025
Bioreactivity of dissolved organic carbon in ponds of the ice-wedge polygonal tundra
Abstract. The role of ponds in transforming laterally exported dissolved organic matter (DOM) within polygonal landscapes affected by degrading ice-wedges remains poorly understood, despite their potential importance in carbon cycling. We hypothesized that the morphological and limnological diversity of ponds–driven by permafrost erosion and soil subsidence–generates DOM of varying bioreactivity. To test this, we conducted a 188-day bioassay using water from 15 ponds representing the main geomorphological pond types in a polygonal landscape in northeastern Canada. Using optical spectroscopy, we examined the relationship between DOM properties and its bioreactivity. We also conducted a parallel bioassay experiment with nutrient additions to assess potential inorganic nitrogen and phosphorus limitations. Results show that a significant proportion of dissolved organic carbon (DOC) is available to bacterioplankton in these shallow lentic systems during summer (33 % decomposed after 97 days). Contrary to our hypothesis, and despite variations in DOM composition, no difference in DOC loss was observed among the three pond categories defined in this study, suggesting comparable bioavailable DOC pools. Moreover, nutrient addition did not significatively enhance DOC loss or decay rates, suggesting that bacterial decomposition depends mainly on organic matter bioavailability. This is further supported by a positive correlation between DOC loss and tryptophan-like fluorophores, a marker of bioavailable DOM. This suggests that DOM released by cyanobacterial mats and other autochthonous producers may be more readily utilized by bacteria than DOM derived from peaty soils. These findings highlight the importance of freshly produced organic matter in regulating carbon cycling in ponds of the ice-wedge polygonal tundra, with consequences on the fate of carbon released from thawing soils.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-5257', Anonymous Referee #1, 11 Feb 2026
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RC2: 'Comment on egusphere-2025-5257', Anonymous Referee #2, 17 Mar 2026
Manuscript review:
Bioreactivity of dissolved organic carbon in ponds of the ice-wedge polygonal tundra
General description:
This manuscript investigates the bioreactivity of dissolved organic carbon (DOC) in ponds located within ice-wedge polygonal tundra landscapes on Bylot Island (Canadian Arctic). The authors conducted an 188-day dark incubation experiment using water from 15 ponds representing three geomorphological pond types (eroding ice-wedge troughs, stabilized ice-wedge troughs, and coalescent polygon ponds). Dissolved organic matter (DOM) composition was characterized using absorbance and fluorescence spectroscopy. The components from a PARAFAC analysis in a previous study were used here, identifying eight fluorescent components. DOC degradation dynamics were evaluated using several decay models, including linear, exponential, exponential with residual pool, and gamma reactivity continuum models. The results show that approximately one third of DOC was degraded within 97 days, but no significant differences in DOC loss were observed among pond categories despite differences in DOM optical properties. Nutrient addition did not significantly enhance DOC degradation, and regression analyses suggest that tryptophan-like fluorescence is associated with higher DOC loss.
Overall, the study addresses an important topic in Arctic carbon cycling, particularly the role of thaw ponds in processing permafrost-derived organic matter. The long incubation period is a notable strength, as we expect a warmer climate with lower precipitation and with longer water residence time. The study is generally well explained, and most sections are clear; however, there are a few instances where further explanation is necessary. It would be good to include estimates of short-term (8-day) decay rates, as they provide valuable input for examining the fast pool of DOM. The discussion would benefit from elaborating upon long-term versus short-term degradation rates (Check the paper by Francois Guillemette et al. 2011) and how different model fittings/comparisons between them help interpret observed trends.
There are some aspects of the experimental design and interpretation of the results that would benefit from clarification or additional discussion. I found the methods section harder to follow, especially regarding the replicates, nutrient-addition treatments, and sample size. Please be clear in figure captions to mention how many samples are included in each grouping. In the discussion, the interpretation of the results could be further developed, rather than primarily restating the findings, and some parts of the reasoning need to be improved.
One important component of the study is the characterization of DOM composition using PARAFAC analysis. It was not entirely clear at first that the PARAFAC model was developed with a larger sample size. The sample size of this dataset is small, but it would be helpful to clarify how many samples from the present study were included in the larger PARAFAC model and how many samples in total were included in the PARAFAC modelling. It would be helpful to see the components in the supplementary information. The current analysis of components based on the maximum fluorescence intensity is limited since fluorescence intensity is highly correlated to DOC concentration. Using the %components would be more suitable for assessing the influence of DOM composition and would exclude the effect of DOC concentration.
Finally, it would be valuable to check the nutrient stoichiometry (C:N and C:P) ratio and its potential impact on the degradation rate of DOC. The study finds that nutrient addition did not increase degradation rates. It could help elevate the discussion by explaining how nutrient stoichiometry in these Arctic systems relates to bacterial stoichiometry and by discussing which nutrients might have been more limiting. For example, see Goodwin et al., 2017 – Ecology 98(3):820-829. doi: 10.1002/ecy.1705.
More detailed comments:
L31. Please specify which Arctic regions or landscape types are being referenced here, as DOM sources and processing pathways can vary substantially among Arctic environments.
L40. Please ensure consistent terminology for the optical techniques. Consider using absorbance instead of absorption.
L40. Absorbance and fluorescence spectroscopy are useful tools for characterizing DOM from different sources, including terrestrial and microbially derived DOM (McKnight et al, 2001; Jaffe, 2008). What do you mean by functional properties? Optical characteristics should not be interpreted beyond their original intention. The PARAFAC components can be related to functional characteristics measured across an experimental gradient, but the components themselves are statistical products of a dataset and identify regions of the EMM that covary within a particular dataset. Is the focus of this study explicitly emphasized in the relationship between different DOM fractions and their bioreactivity?
L42. Since the manuscript later relates protein-like fluorescence to DOC bioreactivity, it would be useful to reference previous studies linking tryptophan-like or tyrosine-like fluorescence components to bioavailable DOM.
L.42. What do you mean by synergetic permafrost deposits? It would be helpful to add one sentence for non-specialists to explain this terminology.
L49. Please check spacing
L67. Please clarify how hydrological connectivity was assessed or inferred for the different pond categories, particularly for coalescent polygon ponds.
L70. I am not sure how the first hypothesis was formulated. Could you provide references here? Thawing the surrounding soil releases DOM from soil pores that were previously trapped there, and this may increase the DOM with a terrestrial signature. So, it is expected that the increase of this fraction reduces the bioreactivity.
L116. The description of the bioassay design does not clearly specify the number of incubation units and the replication structure. In particular, it is unclear how many replicate bottles were incubated per sample, how many were nutrient-amended versus unamended, and whether nutrient additions were applied in parallel to control incubations for each sample. The term “replicate incubation units” is introduced without prior definition. Please clarify the number of replicates per treatment and provide a concise summary of the experimental design (e.g., n per treatment, ± nutrient additions). It should be clear to the reader how many samples were included in each analysis and is included in each figure.
L.118. Please explain here the rationale for the selected concentrations of the nutrient additions.
L.120. Is there a reason that 188 days was chosen as the final incubation time? As it is longer than one growing season.
L.129. Were the samples acidified for storage, and if so, how long were the samples stored before analysis? Or alternatively, was the measurement done right after adding the acid? Was any flocculation observed in the samples due to changes in pH, and how long were the samples kept before DOC analysis? A pH of 2 is very low, and some fraction of the DOM is likely to become insoluble if there is a long delay between adding acid and the measurement. Please clarify this section of text.
L145. In the reactivity continuum model, υ describes the shape of a continuous reactivity distribution and the relative contribution of slower-reacting compounds, not a direct measure of abundance or fraction in DOC pools. Clarification or more cautious wording would be appropriate.
L148-154. The last paragraph in section 2.4 is more about results than the method section. It can be moved to section 3.3.
L155. Please state the sample storage duration prior to DOM optical analyses.
L.170. I understand that PARAFAC analysis was done in a previous study (Pacoureau et al 2025), but the explanation could be clearer (e.g., sample size of the larger dataset and a description of the larger dataset). How was the existing parafac model done? Please provide the PARAFAC components in the supplementary information. This section could be explained more clearly since the dataset in this study is small relative to the number of derived components.
L.195-199. The multiple linear regression analyses based on pooled data from 15 ponds and all-subsets model selection are potentially sensitive to overfitting and multicollinearity. As there is strong covariance among DOM optical and chemical predictors, a multivariate approach such as partial least squares regression (PLSR), with appropriate cross-validation, may provide a more robust alternative for relating initial DOM properties to DOC loss metrics.
L.200. I wonder if a mixed-effect model would be more appropriate than two-way mixed measures ANOVA, as there is a repeated measure structure? Please explain the motivation for the decision.
L.226. Consider altering the title. The current title does not clearly reflect questions related to nutrient additions, pond types and DOM composition.
L.245. Could you also include pH, C:N, and C:P ratios in Table 1? It would be useful to examine the stoichiometry and compare with other studies in the discussion. Particularly in reference to the discussion about why nutrient additions did not influence bioreactivity.
L.240. In general, the DOM composition is not statistically different in SIWT and CP for all components except HT2. It is interesting that microbial humic-like is higher in eIWT with a higher tryptophan peak in P1. And in general, the mean of the protein-like component is not different among them. This could be explained more in the discussion. Can it be due to more DOM degradation in eIWT ponds? It could help refine the interpretation of DOM sources and processing.
L.250-261. The presentation of DOC loss results (Figure 2) could be clearer, particularly the distinction between differences among pond categories, differences across incubation time, and the nutrient effects (using different colors or shapes in the box plot could help clarify). Are the nutrient-replete samples included in the box plot? Also, why didn’t you include the short-term changes in DOC over 8 days in this box plot? I think either panel A or B would be ok to include in the main text.
L265. In Figure 1, fluorescence intensity is shown for different components obtained from PARAFAC. Given that DOC concentrations differ among pond categories, it would be helpful to clarify whether differences in Fmax reflect changes in DOM composition or simply differences in overall DOC concentration. Consider presenting the %component to show the relative contributions of components and facilitate the interpretation of compositional differences. The Fmax is of limited use to draw conclusions from since concentration is embedded in the intensity. Since the PARAFAC components are not available to see visually, it is hard to know if two or three of the components are redundant and could be merged into one. Components should always be provided to readers so that they can see their shapes – for example, one can see if they are a single peak or a double peak.
L.270.Please be consistent in figure names, either figure or fig
In section 3.3, L278, please state that the results are derived from an exponential model with a residual component. Also, include the justification for choosing this model over others, as noted in the comment above. One strong point of this study is the comparison of model fits. It is useful to give a clear discussion about the advantages or disadvantages of the different models.
L.285. It would be good to include the statistical results of the linear regression in the SI
L.295. Figure 3. Under nutrient-replete conditions, the changes in DOCt/DOC0 appear more variable, particularly among certain eIWT and sIWT ponds. It would be useful to comment on whether these ponds shared any distinctive initial characteristics. Did you statistically check if DOC decomposition varies across pond categories in nutrient addition treatments? This seems to be an important missing analysis.
L.295. Figure 3. Please display the observed DOCt/DOC0 data points together with the fitted decay curves. Currently, the reader only sees the fitted curve. Without the data points, it’s hard to visualize how well the model fits the experimental data.
L.315. Did you consider checking the normalized decay rate over DOC concentration (k/DOC)? This can help eliminate the influence of DOC concentration, as the focus of the study is on evaluating differences in DOM composition.
In Figure 5, please revise the figure caption; the x-axis of the figure 5c needs to be described
L.309. The discussion refers to water residence time, but it was not directly measured in this study. This connection should therefore be framed more cautiously or supported more explicitly using previous hydrological work at the site.
L.320. How negligible is this in comparison to this study? Not sure if the dry season could be a good explanation, as drier seasons might increase the WRT and could also reduce terrestrial input. Overall, I think it’s good to discuss more and elaborate further in the discussion.
L.324. Please clarify comparable duration - how many days of incubation?
Section 4.1. The authors observed significant differences in DOM composition but similar DOC loss across pond types. It has been discussed that DOC changes over time, and the plateau in DOCt/DOC0 represents the DOM pools, which could be due to the depletion of the labile fraction. Further elaboration on the study results is needed to show that the remaining DOC fraction is mainly from a recalcitrant pool. How do different peaks from fluorescence methods change as the data were collected over different days of incubation?
References:
Guillemette, F., & del Giorgio, P. A. (2011). Reconstructing the various facets of dissolved organic carbon bioavailability in freshwater ecosystems. Limnology and Oceanography, 56(2), 734-748.
McKnight, D. M., Boyer, E. W., Westerhoff, P. K., Doran, P. T., Kulbe, T., & Andersen,
- T. (2001). Spectrofluorometric characterization of dissolved organic matter for indication of precursor organic material and aromaticity. Limnology and Oceanography, 46(1), 38-48.
Jaffé, R., McKnight, D., Maie, N., Cory, R., McDowell, W. H., & Campbell, J. L. (2008). Spatial and temporal variations in DOM composition in ecosystems: The importance of long-term monitoring of optical properties. Journal of Geophysical Research: Biogeosciences, 113(G4), 4032.
Goodwin et al., 2017 Growth rate and resource imbalance interactively control biomass stoichiometry and elemental quotas of aquatic bacteria Ecology 98(3):820-829. doi: 10.1002/ecy.1705.
Citation: https://doi.org/10.5194/egusphere-2025-5257-RC2
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- 1
Review of the manuscript titled “Bioreactivity of dissolved organic carbon in ponds of the ice-wedge polygonal tundra”, proposed by Thomas Pacoureau, Milla Rautio and Isabelle Laurion.
This study tried to describe processes surrounding the dynamics of the dissolved organic carbon (quantity and quality), specifically for a variety of defrosted Arctic ponds under the short summer season. For this matter, Pacoureau et al. have associated a sampling of environmental reference forcing conditions with a controlled laboratory experiment to reproduce DOC loss over the season under heterotrophic conditions. The experiment is doubled with a nutrient-enriched essay to test the second hypothesis of work on the drivers limiting microbial biomass growth. The dissolved organic carbon is studied under the spectrum of its concentration for the quantitative part and under the spectrum of its optical properties for the qualitative part. Finally, Pacoureau et al. concluded that beyond a homogeneous loss of DOC over ponds and to the end of the season, it is the lability of the DOC that showed correlations with pond-types and the environmental conditions, opening the discussion over global change effects on such ecosystems.
Global critic
Globally, I enjoyed discovering this study, the scientific strategy, its results and the biogeochemical processes finally highlighted. Besides, I found a consistent and well-written text (almost all the time) easy to follow and understand. However, there is for me one structural issue that I will detail below, in addition to minor questions or remarks. To resume the minor remarks, I mainly found terms or phrases vague or ambiguous, needing more precision and justification.
Autotrophic processes and the global carbon cycle
As a scientific strategy, you chose to minimise the autotrophic processes in your experiments, but it must be acknowledged that, finally, the labile OM provided is essential in explaining the DOC loss dynamics. There are structural gaps in its integration of it, from the beginning to the end. As you saw, chlorophyll a levels are quite high, meaning an active local living biomass of phytoplankton, maybe also the mat of cyanobacteria, providing protein-like DOC, and the microbial compartments consumed it preferentially until 90 days (why the plateau?). One parameter, phaeopigments, would have really tested all your grey areas. As a proxy of the decayed photoautotroph cells, it would have better accounted for the cyanobacteria mats (more phaeo than chla since it is not in the water), and quantified the labile POM pool besides the P1-P2 dynamics. Maybe as a hypothesis, all the chla+phaeo have been consumed at D+90 (or is it another nutrient that is limiting? Unfortunately, it's not discussed). Also, there is no discussion about the link between phytoplankton (and microphytobenthos including cyanobacteria) and the bacterial compartment, known to be strongly intricated in quantity and quality (Costas-Selas et al., 2024; Liénart et al., 2020). Finally, I craved for a better discussion integrating the relationships of decreasing decay while a360 increasing, DOC loss and P1 intensity in terms of the global carbon cycle. What do your (great) findings tell us about the carbon qualitative dynamics of the region (4.6 to reshape)? I do not see a clear statement to conclude strongly the discussion, where flux biogeochemists will use your paper(s) to clearly state: What does this new understanding about heterotrophic consumption of DOC tell us about the exchanges between compartments? What is the specific role of such aquatic ecosystems in the global carbon cycle (in view of the current knowledge, Chaplot and Mutema, 2021)? Maybe a conceptual synthesis figure is the only answer to this last point.
Abstract
l.11-12: Maybe the concept of “ice-wedge polygonal tundra” is a little too niche to not be defined even in the abstract. For you to see.
l.18: “in these shallow lentic systems” seems awkward to be recalled here.
l.20: The pond types have to be called at least, and they do not originate from this study, so just call them.
Introduction
l.32-33: Are 5 references really necessary?
l.34: Vegetation has not been introduced yet; it has to be done earlier to understand what primary producers (living or decayed) exist in such a particular ecosystem.
l.47: I suppose you used “watershed” for its American meaning of surface of catchment. I suggest that for all English users, you use a less ambiguous term (catchment, basin, drainage area, etc.).
l.63-64: The description of the three types of ponds is simple and clear, but introduced ambiguously. I don't understand what "representative" means here. You have already established that there are only three types of ponds in these systems, so it seems clearer to me to say "the three types of ponds that can be found in ...".
Material and methods
Study site: I found in Pacoureau et al. 2025 the study site figure I wanted, firstly to understand personally what a polygonal ice-wedge tundra is and what the ponds look like, and secondly to check why there is nothing graphical in this Method. I know that after an analogous paper about the same site, you are tempted to resume the Material and Methods for the next one, but as proof, I was not able to understand this article without seeing the previous one. I would like to see a more detailed description of the study site, something between the actual version and the Pacoureau et al. 2025 one.
MLR: I have some questions about the statistics. Why did you choose to perform only multiple linear regressions, and not general linear models, that would have permitted testing more distributions than the simple Gaussian one, also avoiding the log transformation for scaling? For the multicollinearity, why Spearman and not the Variance Inflation Factor (Borcard et al., 2011)? Why the AIC and not the BIC? You do not mention whether you checked that you retained models only if all the variables were significant. I suggest testing those, or justify why not.
l.83-84: I understand that there is 78 mm of precipitation on average in total over the 3 months. This should be marked more clearly to avoid confusion (with monthly precipitation).
l.106-108: I don’t understand. Smaller than what? I understood above that you used a greater mesh size than usual, to retain more bacteria, but always excluding bacterivores. Either a word is false, or the paragraph should be clearer.
l.112-115: Unless I am mistaken, you are not taking this bias into account in the discussion on the DOC loss.
l.126: naïve question, why a 29-day basis for a month and not 30 or 31?
l.127-128: Please specify the GF75 grade, not to mistake the filter properties with the GF/F one
l.133-135: I suggest displaying the equations as a synthesis, at least for the complex exponential one (which is prominent later).
Results
3.1: Chlorophyll a levels are quite interesting; you should acknowledge them to discuss more about the trophic level later (associated with the nutrient-based part of the discussion). Fmax of microbial-like and protein-like are at the same level, is not it interesting to note it in view of the discussion?
3.2: Good
3.3: Good. I am just wondering if the information carried by the figure 4 is sufficient to be a whole figure, or if it cannot be mixed with fig. 3 or just put as a table.
3.4: As it stands, the figure 6 is badly exploited. I had to go to Pacoureau et al. 2025 to figure out what the EE signature of P1 was, finally to see that the scales are not the same for each pond type. It is not correct. For me, EEMs have a quantitative lecture, so you have to homogenise the scales. Then you will be able to describe it, comparing the ΔRU but also between the ponds.
l.232-233: The form could be better.
Discussion and conclusion
I found the discussion pleasant, well-structured and written, outside of the global criticism.
L389-390: You should check your writing around the nutrient mentions (here the C:N and C:P ratios), where you forget to mention “dissolved”, I know that it seems obvious for you, but not for those who juggle between dissolved and particulate.
4.5: I find this part of the discussion a bit too advanced (l.410-411), as you voluntarily focused your experiments on the heterotrophic processes; even if you have found a great residual DOC pool, you don’t know the amplitude of action of photodegradation and primary production, for example. Independently, some insights about what forcings can be responsible for resuspension (l.414-415) will deepen this paragraph.
l.426-427: the reverse is also true from POM to DOM (Hu et al., 2022).
l.439: The first sentence of the conclusion is decisive, and it should be more precise. I suggest either adding a bio-essay (or experiment) around or replacing “estimation”, and/or adding heterotrophic or microbial to “DOM decomposition”.
l.420: As for the abstract, I do not understand your use of “morphological” and “limnological”, terms that are vague to me. I found in your article a comparison of pond types, led by their hydro(geo)morphology, and a comparison of nutrient levels, so biogeochemistry.
Suggestion to the editor
As a synthesis, I found that the science carried by this manuscript, after intermediary corrections, will be a matter of interest and advances and should be disseminated to the scientific community in this journal.
References
Borcard, D., Legendre, P., and Gillet, F.: Numerical Ecology with R, Springer, 315 pp., 2011.
Chaplot, V. and Mutema, M.: Sources and main controls of dissolved organic and inorganic carbon in river basins: A worldwide meta-analysis, Journal of Hydrology, 603, 126941, https://doi.org/10.1016/j.jhydrol.2021.126941, 2021.
Costas-Selas, C., Martínez-García, S., Delgadillo-Nuño, E., Justel-Díez, M., Fuentes-Lema, A., Fernández, E., and Teira, E.: Linking the impact of bacteria on phytoplankton growth with microbial community composition and co-occurrence patterns, Marine Environmental Research, 193, 106262, https://doi.org/10.1016/j.marenvres.2023.106262, 2024.
Hu, B., Wang, P., Wang, C., and Bao, T.: Photogeochemistry of particulate organic matter in aquatic systems: A review, Science of The Total Environment, 806, 150467, https://doi.org/10.1016/j.scitotenv.2021.150467, 2022.
Liénart, C., Savoye, N., Conan, P., David, V., Barbier, P., Bichon, S., Charlier, K., Costes, L., Derriennic, H., Ferreira, S., Gueux, A., Hubas, C., Maria, E., and Meziane, T.: Relationship between bacterial compartment and particulate organic matter (POM) in coastal systems: An assessment using fatty acids and stable isotopes, Estuarine, Coastal and Shelf Science, 239, 106720, https://doi.org/10.1016/j.ecss.2020.106720, 2020.