Biogeochemical stability of organic covers and mine wastes under climate change simulated mesocosms
Bibliographic record
Abstract
Mine environments in boreal and sub-boreal zones are expected to experience extreme weather events, increases in temperature, and shifts in precipitation patterns. Climate change impacts on geochemical stability of tailings contaminants and reclamation structures have been identified as important climate-related challenges to Canadian mining sector. Adapting current reclamation strategies for climate change will improve long-term efficiency and viability of mine tailings remediation/restoration strategies under a changing climate. Accordingly, mesocosm experiments were conducted to investigate associations of climate-driven shifts in microbial communities and functions with changes in the geochemistry of organic covers and underlying tailings. Our results show that warming appears to significantly reduce C:N of organic cover and promote infiltration of nitrogen into deeper, unoxidized strata of underlying tailings. We also observed an increase in the abundance of some nitrate reducers and sulfide oxidizers in microbial communities in underlying tailings. These results raise the concern that warming might trigger oxidation of sulfide minerals (linked to nitrate reduction) in deeper unoxidized strata where the oxygen has been eliminated. Therefore, it would be necessary to have monitoring programs to track functionality of covers in response to climate change conditions. These findings have implications for development of climate resilient mine tailings remediation/restoration strategies.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".