Mercury in vegetation and organic soil at an upland boreal forest site in Prince Albert National Park, Saskatchewan, Canada
Bibliographic record
Abstract
We studied an upland boreal forest plot located in the Prince Albert National Park, Saskatchewan, Canada, to measure the total mercury content in vegetation and organic soil with a view to assessing the potential for mercury release during forest fires. The study area consists of two stands of vegetation regrown after fires 39 and 130 years ago, with different carbon and mercury stocks in vegetation and organic soil. The mercury concentrations in ng g −1 (dry weight) were measured for moss (90–110), leaves (8), needles (10), bark (16–38), lichen (30–227), bole wood (2) and for organic soil layers (120–300). The combined mercury stock increased from 1.01 ± 0.28 to 3.45 ± 0.87 mg m −2 for the two stand ages; 93–97% of the mercury resided in the organic soil to the mineral layer. The mercury input to the ecosystem is from wet and dry deposition and is trapped in the organic soil layers as indicated by the high organic soil mercury concentrations and low mercury concentration in the underlying mineral layer. Extrapolation from the data measured for the two subplots to all boreal forests suggests a massive mercury stock in boreal forests (15,000 to 44,000 t). This is a low estimate because boreal lowlands have still higher mercury densities. Not all of the organic soil mercury was acquired since the last burns; some predates the more recent fires. The mercury being predominantly located in the organic soil makes fire severity the most important parameter for mercury release. The anticipated accelerated warming in northern latitudes would increase severity, frequency and burn area of future fires and result in large pulses of mercury to the atmosphere and further stress to the environment.
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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 | 0.001 | 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".