Articles | Volume 22, issue 23
https://doi.org/10.5194/bg-22-7929-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Bioaccumulation as a driver of high MeHg in the North and Baltic Seas
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- Final revised paper (published on 11 Dec 2025)
- Supplement to the final revised paper
- Preprint (discussion started on 22 Apr 2025)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on egusphere-2025-1486', Anonymous Referee #1, 05 Jun 2025
- AC1: 'Reply on RC1', David Amptmeijer, 15 Jul 2025
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RC2: 'Comment on egusphere-2025-1486', Anonymous Referee #2, 15 Jun 2025
- AC2: 'Reply on RC2', David Amptmeijer, 15 Jul 2025
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
ED: Publish subject to minor revisions (review by editor) (15 Aug 2025) by Jane Kirk
ED: Publish subject to minor revisions (review by editor) (18 Aug 2025) by David McLagan (Co-editor-in-chief)
AR by David Amptmeijer on behalf of the Authors (18 Sep 2025)
Author's response
Author's tracked changes
Manuscript
ED: Publish as is (02 Oct 2025) by Jane Kirk
ED: Publish as is (03 Oct 2025) by David McLagan (Co-editor-in-chief)
AR by David Amptmeijer on behalf of the Authors (18 Oct 2025)
Post-review adjustments
AA – Author's adjustment | EA – Editor approval
AA by David Amptmeijer on behalf of the Authors (24 Nov 2025)
Author's adjustment
Manuscript
EA: Adjustments approved (03 Dec 2025) by Jane Kirk
This manuscript investigates the impact of bioaccumulation in marine mercury (Hg) cycling, highlighting how ecosystem feedbacks can lead to higher concentrations of Hg in water (compared to an abiotic system, i.e. the status of many Hg cycling models), as well as seasonal and spatial differences in the magnitude of these effects across the North and Baltic Seas. These feedbacks are quantified through coupling a marine ecosystem model that incorporates mercury bioaccumulation, mercury cycling model, and hydrodynamic model in a fully online way for a 1D column model, and offline for a 3D model that allows for exploration of spatial variation. The study presents sophisticated model coupling, generally clear model evaluation, and well-designed model experiments. Overall, I found this manuscript to be an important and timely contribution, that makes a strong case for representing ecosystem effects on mercury cycling “even in cases where bioaccumulation is not of direct interest,” for both improved scientific understanding and environmental management. However, I believe the manuscript could benefit from revisions that focus on improved presentation, clarity, and contextualization of results, before publication, to maximize its impact and uptake.
MAJOR COMMENTS
1) While I recognize that this is a complex model and study design, the manuscript is on the long end, and there may be opportunities to streamline the text (particularly in 2.2-2.7) to avoid repetition and allow the core messages to come through more clearly. The authors could consider using a supplemental information section to present some details of model assumptions and parametrization, as well as for some supporting figures (e.g., Figure 12). In addition, the manuscript would benefit from additional review for typos and readability. Some have been flagged below in minor comments.
2) It could be helpful to provide a brief summary of the drivers of spatial and temporal variation in the results, as some of these details may be contained in the cited original model papers and therefore less clear to a reader. For example, for seasonality: to what extent is temperature dependence also considered in the bioaccumulation and toxicokinetic modeling, in addition to biomass modeling? For spatial variation: What determines the spatial distribution of higher trophic levels? Is migration relevant, and if so, how is it considered? If not, what additional implications could this have for the spatial dynamics?
3) See below for some places where clarification of some methodological details could be beneficial, potentially in supporting material (e.g., in model-obs comparison for 1D, initial conditions).
4) The authors may have the opportunity to deepen the reflection on next steps and future directions, given the importance of the call to better represent ecosystem effects in models. Some questions I am particularly curious to get their thoughts on are: a) is model coupling the only way to do this, is it reasonable to do a back-of-the-envelope adjustment factor that is regionally specific; b) how much trophodynamic complexity is needed — does capturing the base of the food web get most of the effect or do fish 1 and 2 shift the patterns; if so, what might be missing in this current simplified representation of the ecosystem
DETAILED COMMENTS
L22: Number of parties now exceeds the number of signatories (over 150), so could update the number https://minamataconvention.org/en/parties
L52: “In summary, there are three fractions… in our model.” Read as confusing as the model hasn’t been introduced yet.
L137: As defined in the first sentence, isn’t this bioconcentration only?
Fig. 1: Typos in title and Scenario C. Could consider overlaying the 1-D vs 3-D component too so that it captures that aspect of the design as well. Could incorporate map of locations as a side panel for global audience.
Section 2.4: Include grid resolution for the 3D models (may have missed this)
L299: pre-dated?
L312-316: A bit more detail on this model tuning/calibration process — what informed the choice of lowered value
L468-472: What are the observed values for biomass? Not sure if I missed their reporting somewhere. Could they also be put on Figure 2 for comparison?
L508: How is “high quality” defined?