Blackfly Larvae (Simulium spp.) Can Intensify Methylmercury Biomagnification in Boreal Food Webs
Bibliographic record
Abstract
Abstract Global pollution of mercury (Hg) threatens ecosystem and human health. We measured total Hg (THg) and monomethylmercury (MMHg) concentrations in filter-feeding blackfly (Simulium spp.) larvae in the inflows and the outflows of six boreal lakes with no Hg point source pollution. THg in the larvae ranged from 0.03 to 0.31 mg kg−1 dw and MMHg between 0.02 and 0.25 mg kg−1 dw. The proportion of MMHg in the larvae was 74 ± 0.16% and ranged from 43 to 98% of THg, the highest proportions being comparable to those typically found in aquatic predatory insects and fish. We compared the larvae MMHg concentrations to river water quality, catchment land-use, and to size-adjusted lake pike THg data. Two of the investigated catchments have been affected by a multimetal biomine since 2008 and were characterized by higher conductivity and higher urban land-use activity. Larvae THg and MMHg concentrations were higher in the lake inflows than in outflows and associated with water conductivity and catchment land-use activity. Lake pike THg concentrations were highly correlated to lake outflow blackfly larvae MMHg concentrations. Our data illustrate that blackfly larvae take up high percentage of THg that is MMHg, which in turn is available for higher consumers in aquatic and terrestrial food webs.
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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 | 0.000 | 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".