Methylmercury Dietary Pathways and Bioaccumulation in Benthic Invertebrates of the Arctic Ocean
Bibliographic record
Abstract
This study investigated drivers of methylmercury (MeHg) concentrations in Arctic benthic invertebrates of the Canadian Beaufort Sea.A combination of carbon, nitrogen and sulfur stable isotopes and fatty acid analysis were used to examine the influence of trophic position and diet on MeHg concentrations in 476 individuals from 51 species of benthic invertebrates from three different feeding guilds.Individuals were assigned to species (n = 30) or higher taxonomic level (n = 21) based on DNA-barcoding along with traditional taxonomy.Biomagnification patterns were characterized across the faunal assemblage with a range in MeHg concentrations from 3 to 421 ng/g (dry weight basis) over three trophic positions (δ 15 N range 4.4-14.2‰).Multivariate models indicate that within the benthic food web, energy sources had small but significant effects on MeHg bioaccumulation.Carbon stable isotopes were weakly correlated to MeHg concentrations for a subset of samples, suggesting terrestrial and benthic energy sources contributed to slightly higher MeHg burdens.Sulfur isotopes were unrelated to MeHg concentrations.Fatty acid analysis revealed that reliance on diatom and aquatic resources resulted in lower MeHg concentrations.Conversely, reliance on dinoflagellate and benthic resources resulted in higher MeHg concentrations.When trophic position and diet were accounted for, site-specific differences in MeHg were observed; specifically, higher MeHg concentrations at a site closer to the Mackenzie River mouth.Although the reasons for this spatial variation remain undetermined, this study suggests that localized exposure accounts for significant variation in MeHg concentrations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".