The impacts of environmental changes on peatland microbial community structure and function
Bibliographic record
Abstract
Northern peatlands store approximately 30% of the world’s soil carbon, and are also responsible for contemporary fluxes of the greenhouse gases carbon dioxide (CO2) and methane (CH4), making them important players in the global carbon (C) cycle. These greenhouse gas emissions are mediated by peat-dwelling microbes; however, the environmental factors governing the structures and functions of peat microbial communities are still poorly understood. In order to better understand these dynamics, I examined the effects of two forms of environmental change on peatland microbial communities. Firstly, to gain fundamental knowledge of the drivers of microbial community shift due to natural peatland succession, I examined the effects of long-term peat transplantation from a rich fen to a late-successional poor fen. This allowed me to evaluate the relative effects of solid phase chemistry and substrate (largely determined by the parent material/vegetation) versus aqueous chemistry (influenced more by groundwater or precipitation sources), on peat microbial communities. My results suggest that solid phase chemistry, particularly total nitrogen (TN) and C:N, may be important in determining the makeup of peatland bacterial communities. Secondly, I examined the effects of soil warming simulating projected climate change in a poor and an intermediate fen on peat microbial respiration and CH4 production as the preliminary stage of a multi-year, large-scale field experiment. Soil warming did not lead to any effects on CO2 production or CH4 flux during peat incubation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".