Vacuum-extraction of peatlands disturbs bacterial population and microbial biomass carbon
Bibliographic record
Abstract
Knowledge concerning the microbial characteristics of natural and post-vacuum extracted ombrotrophic peatlands, as well as peatlands under restoration is limited. In one experiment, microbial comparisons of paired neighboring natural and post-vacuum peatlands in eastern Québec (Canada) were studied to assess the effects of peat mining on microbial indicators and nitrogen (N) cycling. Microbial counts, microbial biomass carbon (MB-C) and N mineralization were examined over two growing seasons. Also, in a second experiment, bio-indicators of the microbial status (microbial counts, MB-C and the quotient of MB-C to total carbon) of one peatland harboring natural, restored and post-vacuum extracted treatments were assessed sporadically over 6 years. The first experiment revealed that peat mining decreased populations of total bacteria, hemicellulolytic and cellulolytic microorganisms and MB-C, but increased peat ammonium content and N mineralization. The bacterial population was found to be lower in the post-vacuum extracted treatment than in natural treatment (control) and under restoration treatment, whereas the actinomycete population was higher in the post-vacuum extracted and restoration treatments than the natural one. Over the 6-year-time course experiment, the MB-C, total C and their quotient revealed a gradual increase in the peatland under restoration, but they remained similar in the post-vacuum extracted peatland treatment. This supports the concept that the total bacterial population and MB-C may be used as an ecological indicator to monitor major site disturbance using paired natural restored peatland. Published by Elsevier Science B.V.
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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 | 0.000 | 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 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".