the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 13 Jan 2026
Buoyancy and polarity driven accumulation of dissolved organic matter in the sea surface microlayer during a phytoplankton bloom
Abstract. The sea surface microlayer (SML) is only 1–1000 µm thick but resembles a biologically and geochemically very active boundary that modulates the exchange of energy and matter between the ocean and atmosphere. Globally, the SML accumulates up to 200 Tg C yr⁻¹ of organic matter, comparable to sedimentation rates on the oceans' seafloor. Yet, the mechanisms governing the accumulation and transformation of dissolved organic matter (DOM) in the SML remain poorly understood. Exposed to rapid changes of physical, biological, and photochemical conditions, the organic matter pool in the SML often shows heterogeneous distribution patterns, and a clear differentiation between SML and underlying water (ULW) is not always captured during in situ observations. In our mesocosm study, we initiated a phytoplankton bloom under controlled conditions, excluding physical influences like currents, waves, and precipitation. We tested three major hypotheses for DOM enrichment and compartmentalisation in the SML: enhanced in situ biogenic production and processing; physicochemical sorting by polarity and buoyancy; and selective degradation. Our results revealed that buoyancy-driven enrichment of DOM in the SML, fueled by local phytoplankton exudates and their subsequent breakdown, is key to DOM accumulation in the SML-during and after phytoplankton blooms. Untargeted ultra-high-resolution mass spectrometry, complemented by functional group analysis via Fourier transform infrared spectroscopy, showed that particulary carbohydrate compounds became highly enriched in the SML. We also found evidence for accumulation of hydrophobic DOM of biogenic origin, such as lipid- and protein-like compounds, but the related polarity-driven compartmentalisation played a minor role. Moreover, no selective bio- and photodegradation patterns in the SML compared to the ULW took place. We conclude that under exclusively biogenic conditions, sugars and sugar-related compounds are the main drivers of SML compartmentalisation, and we suggest that phytoplankton-induced "carbo-slicks" could be the pioneer stage of a succession of SML organic geochemistry in natural environments.
- Preprint
(1950 KB) - Metadata XML
-
Supplement
(1239 KB) - BibTeX
- EndNote
Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-6563', Anonymous Referee #1, 29 Jan 2026
-
RC2: 'Comment on egusphere-2025-6563', Anonymous Referee #2, 24 Feb 2026
General comments:
This manuscript presents a very nice coupling of data from DOC and DN analyses, SPE-extraction efficiencies, and negative ionization ESI FT-ICR-MS and ATR-FTIR characterization of SPE extracted DOM to investigate DOM in the surface microlayer and in bulk underlying water during a mesocosm experiment mimicking a North Atlantic phytoplankton bloom. It should be of interest to BG readers and is generally well-written and presented. There are, however, a few areas that the authors should clarify their discussions and perhaps modify their presentation of the data. I would also encourage them to add more information about the biological succession in their mesocosm, if they have that information. Knowing what the bacterial response to the blooms was (even just in cell counts per L) and whether there was significant zooplankton grazing would add additional context for their results.
My first general concern is that the authors need to highlight earlier in the paper that SPE-extraction fractionates against carbohydrates and proteins; carbohydrates in particular are not well retained by the resin they use. Negative ionization ESI-MS also has some blind spots as it has low carbohydrate and protein ionization efficiencies. The authors do mention both these points later in the manuscript but they should explicitly discuss these issues in the introduction. Since their data, even with the suppressed carbohydrate response, shows carbohydrates to be important, I wonder if the authors might include in their discussion some of the ultrafiltration-of-DOM literature, where the isolated higher molecular weight DOM was often considered mainly carbohydrate and protein material (early work by Repeta and Aluwihare might be interesting in this regard).
My second concern involves the FTIR data and discussion. FTIR response factors vary considerably depending upon the dipole moment changes of the functional groups being measured. That is why C-H and aromatic bond signals are low relative to C=O and C-O-C in organic compounds even when there are plenty of the C-H and aromatic groups present. Because of this, FTIR is inherently a qualitative characterization tool, though I do think looking for changes in response of different functional groups is valid. I do wonder about normalizing FTIR response to carbon content of the initial sample, rather than total FTIR signal. Most papers I have read have used total signal as a way to adjust for the fact that loading the same amount of sample reproducibly and to the same sample thickness each time is very hard to do in an ATR cell (or in a KBr pellet, for that matter).
Additional more specific concerns follow:
- In lines 112-113, what was used as inoculant or did you just rely on regrowth from cells that survived the initial water treatments?
- In lines 129-130, do you have any idea how much surface-active material you lost in filtering for DOC in both the SML and the ULW? Does this differ with the different filter types you used for processing samples for, say, DOC and DN relative to SPE-extraction?
- Line 155, was this mercury (I) or mercury (II) chloride?
- Lines 177-178. I really like that you calculated extraction efficiency!
- Lines 265-280. Usually this is addressed by normalizing to total (background corrected) FTIR signal response, as depending upon analyst, humidity, cleanliness of cell, variable surfactant levels and sample heterogeneity, reproducibility is variable, even for replicate aliquots of the same sample. Following up on this theme, can you give examples of how variable your replicate analyses are: 1. initially, 2. upon normalization to total response, and 3. with your carbon rescaling technique? Perhaps this could be added to the supplemental section?
- Lines 363-364. I don’t really see this trend for the ULW in Figure 5, and there is a strong and opposite trend for the SML that you don’t mention here.
- Lines 365-368. Why spend so much time talking about O/H? The DOC-DON trend also looks interesting (maybe even more interesting) and isn’t described at all.
- Line 442. You are not studying the low molecular weight fraction but only the fraction retained on an SPE filter (mainly a polarity separation).
Citation: https://doi.org/10.5194/egusphere-2025-6563-RC2
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 174 | 88 | 20 | 282 | 41 | 14 | 17 |
- HTML: 174
- PDF: 88
- XML: 20
- Total: 282
- Supplement: 41
- BibTeX: 14
- EndNote: 17
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Review of the manuscript ”Buoyancy and polarity driven accumulation of dissolved organic matter in the sea surface microlayer during a phytoplankton bloom“ by Zobelein et al.
The authors investigated the evolution of the sea surface microlayer (SML) during an artificially induced phytoplankton bloom in a mesocosm experiment. Using this approach, they aimed to identify the major film-forming organic matter, assess the influence of polarity and organic matter buoyancy, and evaluate the role of photodegradation.
There are too many abbreviations used throughout the manuscript. I suggest minimizing their use, and in particular reconsidering the abbreviation “MF” for molecular formula.
In light of the growing emphasis on Open Science, I do not think the manuscript should be published unless the raw data are made openly available, either through a public repository or in the Supplementary Materials.
L 60 - ... the OM composition ...
L 76 - ... in the SML...
L 155 – What was the final concentration of HgCl2 in the sample?
L 350 – 364 – It was not easy for me to follow the text and Fig. 4. I suggest providing more detailed connections between the text and the sub-figures. For example, the sentence: “In contrast, increasing SML compartmentalisation was noticed for the intensity weighted molecular lability boundary (H/C > 1.5, MLBwL), the humic-like fluorescent DOM (FDOM), and finally the w.a. of carbohydrate-, lipid- and protein-like fractions of the DOM pool (Fig. 4 b, h, i, k, Tab. 2).“ should be written as follows: In contrast, increasing SML compartmentalisation was noticed for the intensity weighted molecular lability boundary (H/C > 1.5, MLBwL) (Fig. 4b) , the humic-like fluorescent DOM (FDOM) (Fig. 4?), and finally the w.a. of carbohydrate-, lipid- and protein-like fractions of the DOM pool (Fig. 4 x, y, z, respectively, Tab. 2).
L 354 – The term “highly unsaturated formula” is not defined anywhere in the manuscript. Please clarify what is meant by this term (e.g., does it refer to compounds with more than a certain number of double bonds?).
L 365-367 – This sentence should be revised for clarity.: While both parameters increased in the SML after the bloom, the latter decreased during the pre-bloom phase, reaching the lowest values in the middle of the bloom phase.
L 369 – Where are these data presented? So, it should be written: The DOC extraction efficiency (EE) (Table 1). According to Table 1, EE is consistently at least 10% lower in the SML than in the ULW, rather than 20%.
L 371 – The term “permeating DOC” is not explained in the main text. This definition should be provided here rather than only in the table caption.
L 373 – EE is mentioned only 3 times in the text so I suggest to use full name.
L 380 – Fig. 4: I would appreciate it if all abbreviations were defined in the figure captions, as repeatedly searching the text for their meanings is time-consuming and tiring.
Also, there is missing y-axis names for 4a, 4c and 4l.
L 434-435_... decreased significantly in the SML...when or where?
L 453 – lipids also may contribute to high DOC/DON ratio
L 459 – Did the authors consider OM photochemical degradation, which often produces oxidized species as an initial step? This may be important particularly for the SML.
L 467 - S5).
L 486 - …in microalgae…
L 499 - C. closterium
L 534 – 535 – I suggest that the authors reconsider this statement. Specifically, alternative explanations should be considered, such as the possibility that POM had already been degraded to CO₂. It is well established that the turnover time of fresh carbohydrates is very short. Harvey et al. (1995; https://doi.org/10.1016/0016-7037(95)00217-N) showed that turnover times among particulate pools are shortest for carbohydrates, ranging from approximately 10.7 days for diatom and cyanobacterial carbohydrates. Furthermore, Becker et al. (2020; doi:10.1073/pnas.1917001117) measured hydrolysis rates of 0.1–34 nmol L⁻¹ h⁻¹, indicating rapid enzymatic degradation of laminarin in the ocean. This comment is particularly relevant given that the mesocosm experiment lasted 33 days, with at least 10 days following bloom decay.
L 585 – Fig. 4l
L 599-600 – I do not understand this sentence: “.... are more affected than ULW in natural environments where light penetration into the water column is limited to depths < 1 m.“ as light typically penetrates much deeper than 1 m in seas and oceans.
L 606, 608, 610, 611 – please write properly E. hux. and C. clos.