Relating Fish Hg to Variations in Sediment Hg, Climate and Atmospheric Deposition
Bibliographic record
Abstract
This article addresses total fish Hg concentrations (THg) by variations in lake Sediment THg, atmospheric Hg deposition (atmHgdep), and climate, i.e., mean annual precipitation (ppt) and air temperature. The Fish THg data were taken from the 1967-to-2010 Fish Mercury Datalayer (FIMDAC). This compilation was standardized for 12-cm long Yellow Perch in accordance with the USGS National Descriptive Model for Mercury in Fish (NDMMF [1]), and documents Fish THg across 1936 non-contaminated lakes in Canada. About 40% of the standardized Fish THg variations related positively to increasing ppt and Sediment THg, but negatively to increasing mean annual July temperature (TJuly). Only 20% of the Fish THg variations related positively to atmHgdep alone. Increasing TJuly likely influences Fish Hg through increased lake and upslope Hg volatilization, in-fish growth dilution, and temperature-induced demethylization. FIMDAC Fish THg effectively did not change over time while atmHgdep decreased. Similarly, the above Fish Hg trends would likely not change much based on projecting the above observations into the future using current 2070 climate-change projections across Canada and the continental US. Regionally, the projected changes in Fish Hg would mostly increase with increasing ppt. Additional not-yet mapped increases are expected to occur in subarctic regions subject to increasing permafrost decline. Locally, Fish THg would continue to be affected by upwind and upslope pollution sources, and by lake-by-lake changes in water aeration and rates of lake-water inversions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".