Seasonal variation in an acid mine drainage microbial community
Bibliographic record
Abstract
Environmental oxidation and microbial metabolism drive production of acid mine drainage (AMD). Understanding changes in the microbial community, due to geochemical and seasonal characteristics, is fundamental to AMD monitoring and remediation. Using direct sequencing of the 16S and 18S rRNA genes to identify bacterial, archaeal, and eukaryotic members of the microbial community at an AMD site in Northern Ontario, Canada, we found a dynamic community varying significantly across winter and summer sampling times. Community composition was correlated with physical and chemical properties, including water temperature, pH, conductivity, winter ice thickness, and metal concentrations. Within Bacteria, Acidithiobacillus was the dominant genus during winter (11%-57% of sequences) but Acidiphilium was dominant during summer (47%-87%). Within Eukarya, Chrysophyceae (1.5%-94%) and Microbotrymycetes (8%-92%) dominated the winter community, and LKM11 (4%-62%) and Chrysophyceae (25%-87%) the summer. There was less diversity and variability within the Archaea, with similar summer and winter communities mainly comprising Thermoplasmata (33%-64%) and Thermoprotei (5%-20%) classes but also including a large portion of unclassified reads (∼40%). Overall, the active AMD community varied significantly between winter and summer, with changing community profiles closely correlated to specific differences in AMD geochemical and physical properties, including pH, water temperature, ice thickness, and sulfate and metal concentrations.
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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 | 0.000 | 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) | 0.001 | 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".