Microbial Community Composition and Activities Across Northern Peatlands
Bibliographic record
Abstract
Northern peatlands are large repositories of carbon and little is known about the effect the microbial community has on carbon mineralization rates, and there is concern that a loss of microbial diversity due to environmental change may lead to reduced ecosystem functioning. Microbial communities vary among peatland types and abiotic variables such as temperature and pH have a large influence on carbon dioxide production, but distinguishing between abiotic controls and the role of microbial community structure has proved challenging. \nMicrobial activity and community composition was characterized in three peatlands within the James Bay Lowlands, Ontario. Similar dominant microbial taxa were observed at all three peatlands despite differences in nutrient content and substrate quality and geographic location. In contrast, microbial activity differed among the sites, indicating that it is influenced by the quality of the peat substrate and the presence of microbial inhibitors. \nA series of reciprocal field and laboratory transplant experiments were conducted at a rich and poor fen near White River, Ontario to more explicitly distinguish between the abiotic and microbial controls on carbon mineralization. The effect of transplantation differed between the laboratory and field studies and when viewed individually could lead to different interpretations of the effect of substrate change. Surprisingly, intensive sampling within both fens was unable to reveal a difference between the rich and poor fen microbial community due to high within site temporal and spatial variation. Thus studies with small sampling effort will have a very incomplete understanding of microbial community structure and thus microbial ecology. \nA reciprocal sterilization transplant experiment was also conducted to examine how different microbial communities adapted to various peat substrates influenced C-mineralization patterns. Post-inoculation/incubation bacterial communities across peatlands converged towards a similar community structure, suggesting that abiotic variables are the dominant control on peatland microbial activity and community composition. \nThe studies presented in this thesis collectively show that across a broad range of temperate and sub-arctic peatland types dominant members of the microbial community are generally similar, and decomposition rates can be predicted by broader controlling environmental factors rather than temporal niche or distributional constraints of the microbial community.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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 teacher head, 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".