Levels of Metals and Microbial Biomass in Cobalt Coleman Mine Tailings (Canada) Three Decades after Land Reclamation
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Bibliographic record
Abstract
<p>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 &gt;100 and 20 &acute; 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 &gt;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&le;0.05) of organic matter compared to non-tailing reference areas. More importantly, the analyses revealed significantly high (p&le;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 non-tailing 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.</p>
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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 it