the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Apr 2025
Feeding strategy as a key driver of the bioaccumulation of MeHg in megabenthos
Abstract. The bioaccumulation of methylmercury (MeHg) in the marine food chain poses a neurotoxic risk to human health, especially through the consumption of seafood. Although MeHg bioaccumulation at higher trophic levels is relatively well understood, MeHg bioaccumulation at the base of the food web remains underexplored. Given the neurotoxic effects of methylmercury on human health, it is essential to understand the drivers of bioaccumulation at every level of the food chain. In this study, we incorporate six megabenthos functional groups into the ECOSMO marine end-to-end ecosystem model, coupled to the MERCY marine Hg cycling model. We investigated how various feeding strategies influence the bioaccumulation of both inorganic Hg (iHg) and MeHg in marine ecosystems. We show that the feeding strategy significantly influences bioaccumulation and correlates stronger with iHg than the trophic level and that suspension feeders have elevated iHg levels while filter feeders have higher MeHg values. Additionally, we show that the bioaccumulation of both iHg and MeHg can be accurately modeled solely based on feeding strategies in low trophic-level megabenthos. However, when modeling higher trophic levels, incorporating the allometric scaling law dramatically improves the model performance. These results demonstrate the need for a holistic approach in which iHg, MeHg, and trophic levels of organisms are evaluated at both high and low trophic levels to identify what food web structures drive high MeHg concentrations in seafood.
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Status: open (until 11 Jun 2025)
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RC1: 'Comment on egusphere-2025-1494', Anonymous Referee #1, 09 May 2025
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General Assessment
This manuscript addresses an important research question concerning mercury (Hg) bioaccumulation at the base of the marine food web. The study is highly relevant to global mercury policy (e.g., Minamata Convention) and human exposure pathways. The paper is well-structured, presents novel insights, and draws clear, well-supported conclusions. However, minor revisions are needed to improve clarity, precision, and flow.
Title and Abstract
- Title: Accurately reflects the paper's content.
- Abstract: Clearly identifies the knowledge gap and purpose of the study. However, on line 7 the sentence “We show that the feeding strategy…” is too long and would benefit from being split into two for clarity.
Scientific Content and Relevance
The study addresses a critical knowledge gap concerning Hg speciation and feeding strategies in marine organisms. It provides novel concepts and models for interpreting bioaccumulation, particularly around the bioavailability and cycling of inorganic and methylmercury. The conclusions are well supported and articulated, particularly those on differences in MeHg vs. iHg across feeding strategies and the implications for risk assessment and modeling.
Examples of valuable contributions include:
- The identification of trophic level 3.6 as a shift point for MeHg dominance in the tHg concentration (section 3.1).
- Lines 316 – 319 provide interesting and relevant insight into how detritus cycling in the Northern North Sea affects Hg transfer. However, I do recommend adding more references in this section.
- Base model and allometric scaling model comparisons revealed useful information on importance of trophic-level-specific MeHg release rate values, and also importance of considering local low-trophic-level species composition.
- Emphasis on the importance of Hg speciation for food web and human health risk assessments.
Structure and Clarity
The structure is logical, and many aspects of the manuscript are very clearly written, for example the feeding strategy descriptions. The main suggestions for improvement would be to increase the number of references, particularly in the methods and discussion sections. The language could also be improved by applying a passive voice and limiting the use of run-on sentences.
Technical Corrections and Suggestions
- On line 18: Add reference for the threefold increase in environmental Hg and specify whether this data is a global average and the environmental medium that it comes from (ie. sediment and peat archives?)
- Line 30: Volume concentration factor (6.4E6) – specify units if applicable.
- Line 31: Sentence is overly casual – recommend removing or revising.
- Line 34: Revise to: “Consumption of MeHg-contaminated seafood is the primary pathway of mercury exposure in humans, with elevated risk among coastal and seafood-reliant populations (Zhang et al. 2021).” This revised version better emphasizes exposure pathways while remaining sensitive to the context of seafood-dependent communities. If you choose to expand on health effects, a brief mention of methylmercury’s neurotoxicity could provide a natural transition to your discussion of Minamata Bay. If you do retain the sentences in lines 34 – 37, also consider briefly clarifying Minamata Bay’s specific contamination source, to not create a false sense of fear that these pollution levels are common.
Reference: Zhang, et al. (2021) Global health effects of future atmospheric mercury emissions. Nat. Commun. https://doi.org/10.1038/s41467-021-23391-7
- Line 39: Rephrase to avoid starting with a number or acronym (e.g., “A total of 151 countries…”).
- Line 95: Add references for the coupled models (ie. GOTM, ECOSMO E2E and Mercy v2.0).
- Alternatively, the subheadings 2.3, 2.4, and 2.5 could be changed to 2.2.1, 2.2.2, and 2.2.3 respectively as they all fall under the “2.2 The models” subheading.
- Figure 1: Uses URL links within the figure caption which is generally not recommended. One possibility for rewording the caption is: “Several sub-images were used to create this figure. Image sources (used under Creative Commons licenses or in the public domain) are as follows: Filter feeder: Sabella spallanzanii (image by Wikipedia contributors, CC BY-SA 3.0, via Wikipedia).”
- Line 148: Provide justification or reference for the bprotected value used.
- Line 155: Maintain consistent MeHg/iHg order throughout the sentence for clarity.
- Line 176: Unsure of what units d-1 refers to.
- Line 210: Include a reference for B10 value interpretation and the Jeffreys–Zellner–Siow prior assumption.
- Line 216: Rephrase for clarity. For example: “A BF10 factor below 1 supports the H1 hypothesis, while BF10 values < 0.1 and < 0.01 are considered strong and very strong evidence, respectively, in favor of the H0 hypothesis.”
- Figure 2 caption: Final sentence seems to have been cut down short. Recommend: “This contrasts the iHg concentration (<100 ng g⁻¹ d.w.) for all animals, except starfish, eel, and sponges.” The caption should also clarify that the data shown came from a literature review. If each point comes from a separate study, consider citing sources directly in the figure legend.
- Line 256: Typo. Should read: “…followed by deposit feeders with up to 5 g C m⁻².”
- Figure 7: Recommend removing plot titles and reformatting to look more like Figure 3. The Hg species should be identified in the y-axis label, and the order of the Hg species should match Figure 3 (MeHg, iHg, tHg). Will also need to be repeated for figure 8.
- Table 2 and 3 captions: Define AS as allometric scaling in the caption only.
Concluding Remarks
The manuscript presents novel and important insights into Hg bioaccumulation and its relationship with feeding strategy, trophic level, and ecosystem cycling. It contributes meaningfully to environmental toxicology and policy-relevant science. With revisions focused on clarity, justification of assumptions, and minor stylistic improvements, this paper will be a strong addition to the journal.
Citation: https://doi.org/10.5194/egusphere-2025-1494-RC1 -
RC2: 'Comment on egusphere-2025-1494', Anonymous Referee #2, 11 May 2025
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The manuscript addresses a timely topic in mercury research by examining how different feeding strategies influence the bioaccumulation of inorganic mercury and methylmercury in marine ecosystems. The results are interesting and potentially valuable to the field. However, the presentation of the results and discussion sections is somewhat unclear and contains redundancy, which makes it difficult to follow the key findings. I also have concerns regarding the model evaluation results and the methodology used for the model assessments. These concerns may be largely addressed if the authors can reorganize and revise the results and discussion section. I outlined my comments below.
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Since the primary objective of the study is to model Hg bioaccumulation, I recommend that the model evaluation be presented as part of the Results and Discussion rather than the Methods. This change would strengthen the narrative and reduce redundancy—many of the points currently discussed in Section 3 could be streamlined. I suggest restructuring Section 3.1 to serve as the model evaluation, followed by subsequent sections explaining key discrepancies between model output and observations (currently in Section 4).
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The purpose of Figure 3 is unclear. It is not evident why the authors chose to use Hg data from different ecosystems and plot them against trophic level (referred to as feeding strategy in the figure). Since ecosystems differ in baseline inorganic Hg and MeHg concentrations, the MeHg–trophic level relationship should be examined within each ecosystem independently.
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For model evaluation, I strongly suggest plotting modeled versus observed concentrations of speciated Hg (inorganic and MeHg) for each modeled feeding strategy. This would provide a clearer and more direct assessment of model performance.
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Section 3.2.3, which addresses the effect of feeding strategy on bioaccumulation, is central to the manuscript’s aims, yet it is not discussed in sufficient depth. In contrast, the manuscript devotes substantial space to explaining Hg vs. trophic level patterns (Section 3.2.4), which are already well-established in the literature. I recommend condensing the discussion in 3.2.4 and focusing more on how feeding strategies influence MeHg and inorganic Hg transfer, particularly in benthic food webs.
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Figure 4 is difficult to interpret. It is unclear whether the data are empirical or simulated. A more straightforward approach might be to present Hg concentrations across feeding strategies as a bar chart with error bars. If the intent is to show correlations between feeding strategies, a correlation coefficient would be more appropriate.
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Section 3.3, on allometric scaling, should appear earlier in the manuscript. When reading Sections 3.2.3 and 3.2.4, I repeatedly found myself wondering about the effects of allometric scaling on the results. Figures 7 and 8 could be consolidated to allow readers to compare model performance with and without allometric scaling more clearly.
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Lines 340–350: This content would be better integrated into the allometric scaling section.
- As the authors note, the model is implemented for the North Sea, yet many of the empirical datasets used for comparison originate from other regions. This mismatch raises concerns about the validity of the model evaluation. Comparing model output to observations from ecologically distinct systems—each with different baseline Hg and MeHg levels, food web structures, and biogeochemical conditions—complicates interpretation and undermines the credibility of the evaluation. I strongly recommend either (1) limiting the model evaluation to observed data from the North Sea, or (2) running separate models parameterized for the specific ecosystems from which the empirical data are drawn.
Citation: https://doi.org/10.5194/egusphere-2025-1494-RC2 -
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