Effects of logging in the southern boreal peatlands of Manitoba, Canada
Bibliographic record
Abstract
To evaluate changes in surface water chemistry, peat, and the plant community in logged peatlands, we compared plots in 1–4 year old (class I) and 9–12 year old (class II) clearcuts with plots in wooded controls. Indicator species were significantly different between wooded and clear-cut plots but not between clear-cut plot age classes. Surface waters in class I clearcuts had significantly higher temperature and nutrients compared with controls, and this was attributed to warming of the soil, which resulted in faster decomposition and greater nutrient availability. Hummocks, important peatland plant microhabitats, were reduced in height in all clearcuts because of compaction and abrasion. These abiotic changes caused a shift in the plant community. Total plant diversity was approximately 30% higher on clearcuts and consisted primarily of herbs, particularly grasses. However, bryophyte and lichen diversity and cover was greatest in wooded controls. Picea mariana (Mill.) BSP regeneration was not compromised by clear-cutting and was greater in class II clearcuts. Greater diversity and cover of Salix species in class II clearcuts suggests stable shrub community formation, which may be persistent and may slow succession. The use of appropriate equipment to minimize site disturbances while the ground is frozen may reduce long-term shifts in the plant community.
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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 | 0.001 |
| 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".