Methylmercury in subarctic amphibians: environmental gradients, bioaccumulation, and estimated flux
Bibliographic record
Abstract
Rapid warming in polar regions is causing large changes to ecosystems, including altering environmentally available mercury (Hg). Although subarctic freshwater systems have simple vertebrate communities, Hg in amphibians remains unexplored. We measured total Hg (THg) in wetland sediments and methylmercury (MeHg) in multiple life-stages (eggs to adults) of wood frogs (Rana sylvatica) and larval boreal chorus frogs (Pseudacris maculata) from up to 25 wetlands near Churchill, Manitoba (Canada), during the summers of 2018-2019. We used egg mass counts for wood frogs from 24 wetlands (2015-2019) and per-ovum MeHg concentrations to estimate site-level MeHg flux by metamorphs from wetlands to the terrestrial environment. Total Hg in wetland sediment was unrelated to MeHg concentrations of amphibian larvae, but sediment THg increased with from coastal tundra vegetation to inland boreal forests. Methylmercury concentrations of wood frog eggs (geometric mean = 35.9; range: 6.7-77.9 ng/g dry wt) exceeded previous reports for amphibians, including from sites contaminated by industrial sources of Hg. Methylmercury concentrations of adult wood frogs (298.9 ng/g dry wt) were also higher than that for frogs included in a recent assessment of MeHg in amphibians across the contiguous United States. Within wetlands, MeHg concentrations of wood frog larvae were strongly correlated with MeHg concentrations in eggs earlier in the summer, and concentrations increased with each life stage. We estimate there would have been 1,971.8-3,286.4 ng MeHg exported from wetlands by wood frog metamorphs, which is 3.4-5.6 times more MeHg than inputted by eggs. Collectively, these data provide an initial assessment of Hg concentrations, body burdens, and dynamics in subarctic food webs that are expected to experience large changes from climate warming.
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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 | 0.001 |
| 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".