Microbial communities and biogeochemical functioning across peatlands in the Athabasca Oil Sands region of Canada: Implications for reclamation and management
Bibliographic record
Abstract
Abstract Peatlands play an important role in global biogeochemical cycles and are essential for multiple ecosystem functions. Understanding the environmental drivers of microbial functioning and community structure can provide insights to enable effective and evidence‐based management. However, it remains largely unknown how microbial diversity contributes to the functioning of belowground processes. Addressing this gap in knowledge will provide a better understanding of microbial‐mediated processes in peatlands that are undergoing restoration or reclamation. This study assessed the changes in microbial community diversity and structure as well as soil function by measuring microbial respiration on a range of substrates from three natural fen types found in the Athabasca Oil Sands region of Alberta, Canada (a poor fen, a hypersaline fen, and a tree‐rich fen) and a nearby constructed fen undergoing reclamation following open pit mining. Overall, substrate induced respiration was significantly higher in the constructed fen. Alpha diversity of fungi and prokaryotes was highest in the tree‐rich fen, and the composition of microbial communities was significantly different between fens. Both fungal and prokaryotic communities were strongly related to pore water pH and temperature, with plant richness also contributing to the shape of fungal communities. In summary, microbial community structure reflects the underlying differences in soil condition across different fens but plays essential roles in the ecological functions of soil. These findings provide a new outlook for the management of peatlands undergoing post‐mining reclamation. Future research on peatland reclamation should consider the dynamic interaction between communities and ecosystem functionality, for which this study forms a useful baseline.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".