Assessing the importance of macroinvertebrate trophic dead ends in the lower transfer of methylmercury in littoral food webs
Bibliographic record
Abstract
Total mercury and methylmercury concentrations ([THg], [MeHg]) were measured in littoral macroinvertebrates from Lake St. Pierre, Quebec, Canada. Functional groups (detritivore, grazer, edible predator, inedible predator) explained the greatest fraction of [MeHg] variation compared with time (year, month), and space (station and shore). Greatest [THg] and [MeHg] were found in inedible predators mostly from families of heteropterans and coleopterans. Detritivores and grazers exhibited the lowest Hg concentrations, while edible predators were intermediate. Inedible predators also had the highest percentage of MeHg ([MeHg]/[THg]), with some taxa close to 100%. Such high percentages are seldom observed in freshwater organisms other than piscivorous fish. MeHg burden (concentrations × biomass) in inedible predators accounted for 10% of the MeHg pool for the whole invertebrate community. These large quantities of MeHg are sequestrated in aquatic “trophic dead ends” and could partly explain the low [MeHg] measured in fish, compared with [MeHg] of macroinvertebrates from Lake St. Pierre and other freshwater ecosystems with large littoral zones. We recommend taking into account the inedible organisms in Hg cycling models to avoid a possible overestimation of the MeHg pool available to fish.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".