Levels of Metals and Microbial Biomass in Cobalt Coleman Mine Tailings (Canada) Three Decades after Land Reclamation
Bibliographic record
Abstract
Investigations of restored metal contaminated tailings in Canada with regard to their long-term ability to sustain plant and associated microbiological populations are limited.The specific objectives of the present study were to assess (1) The current levels of total and bioavailable metals and (2) Microbial biomass in Cobalt Coleman mine tailings reclaimed in 1990.The level of microbial biomass was determined using Phospholipid Fatty Acid analysis (PLFA).Metal analysis revealed that the concentration of total Arsenic (As) was >100 and 20 ´ higher in the Nipissing tailing compared to the non-tailing site and the Cart Lake tailing.The same trend was observed to a lesser degree for total Cobalt (Co) and Copper (Cu) concentrations.Overall, the total metal levels remain high >30 years after phytoremediation, but the bioavailable metal amount was low.This suggests that soil metal impacts on biota are minimal.The reclaimed tailing exhibited significantly lower levels (p≤0.05) of organic matter compared to non-tailing reference areas.More importantly, the analyses revealed significantly high (p≤0.05)total microbial biomass in non-tailing soil samples (with higher organic matter content) compared to tailing soils.A strong positive correlation (r = 0.87) was observed between organic matter and total microbial biomass.In contrast to other studies, the pH of the two tailing sites was neutral (7.1 and 7.5) and negatively correlated (r = -95) with bacterial and fungal abundance.Bacteria dominated the microbial communities in all the sites including the nontailing area, indicating that the targeted region is still under severe environmental stress.Overall, the metal levels in the targeted tailings remain high and the phytoremediation did not improve significantly the soil quality (organic matter, microbial biomass) over the last three decades.
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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 | 0.001 | 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".