Active Layer Thermal Properties and Vegetation Recovery at a Site Experiencing Acid Drainage Near Eagle Plains, Yukon Territory, Canada
Bibliographic record
Abstract
Acidic waters flowing over pyrite-rich shales are discharging near Eagle Plains, Yukon Territory, degrading the local vegetation and permafrost. Initial site investigations in 2005 found that high active layer soluble ion concentrations are likely preserving a supra-permafrost talik that recycles acidity from year to year. Using ground temperature measurements, we have determined that the loss of surface vegetation at the site has resulted in a 4°C to 6°C increase in ground surface and active later temperatures and a 1.7 to 5.1 times increase in active layer thermal diffusivity. Modeling has further shown that the change in energy balance at the ground surface accounts for the permafrost degradation at the site, and that the increased thickness of the active layer is sufficient to preserve the talik even under low salinity conditions. The thawing permafrost has however improved drainage and results in less surface runoff and improved groundwater flow that has disseminated acidity and contaminants throughout the active layer, leading to surface conditions that are more conducive to plant colonisation. Field investigations and analysis of satellite imagery demonstrate that this has reduced the surface expression of area affected by acid drainage by 53% from 2014 to 2021, and that successional changes in vegetation are occurring. Given long enough time periods, this may act as a negative feedback to permafrost degradation and allow the site to recover from past deterioration.
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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 | 0.001 |
| 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) | 0.001 | 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".