Bioaccumulation of methylmercury within the marine food web of the outer Bay of Fundy, Gulf of Maine
Bibliographic record
Abstract
Mercury and methylmercury were measured in seawater and biota collected from the outer Bay of Fundy to better document mercury bioaccumulation in a temperate marine food web. The size of an organism, together with δ13 C and δ15 N isotopes, were measured to interpret mercury levels in biota ranging in size from microplankton (25μm) to swordfish, dolphins and whales. Levels of mercury in seawater were no different with depth and not elevated relative to upstream sources. The δ13 C values of primary producers were found to be inadequate to specify the original energy source of various faunas, however, there was no reason to separate the food web into benthic, demersal and pelagic food chains because phytoplankton has been documented to almost exclusively fuel the ecosystem. The apparent abrupt increase in mercury content from "seawater" to phytoplankton, on a wet weight basis, can be explained from an environmental volume basis by the exponential increase in surface area of smaller particles included in "seawater" determinations. This physical sorption process may be important up to the macroplankton size category dominated by copepods according to the calculated biomagnification factors (BMF). The rapid increase in methylmercury concentration, relative to the total mercury, between the predominantly phytoplankton (<125μm) and the zooplankton categories is likely augmented by gut microbe methylation. Further up the food chain, trophic transfer of methylmercury dominates resulting in biomagnification factors greater than 10 in swordfish, Atlantic bluefin tuna, harbour porpoise, Atlantic white-sided dolphin and common thresher shark. The biomagnification power of the northern Gulf of Maine ecosystem is remarkably similar to that measured in tropical, subtropical, other temperate and arctic oceanic ecozones.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".