Harvesting and slash piling affects soil respiration, soil temperature, and soil moisture regimes in Newfoundland boreal forests
Bibliographic record
Abstract
The effect of harvesting and slash piling on soil respiration, temperature and moisture was examined in a balsam fir (Abies balsamea) and a black spruce (Picea marinara) forest located in western Newfoundland, Canada, 2 mo to 2.5 yr following harvesting. Within 4 mo of harvesting, soil temperature, moisture, and soil respiration rates were affected by harvesting and slash piling. Clearcut areas without slash (CC-S) had significantly lower soil respiration rates than uncut forests (F). However, clearcut areas with slash cover (CC+S) had significantly higher soil respiration rates than CC-S. When harvested areas with and without slash were combined, harvesting decreased soil respiration in the black spruce forest but had no effect on soil respiration in the balsam fir forest. Harvesting increased soil temperatures at 10 cm, however CC+S temperatures were cooler than CC-S temperatures. Harvested areas tended to dry faster than F, although soil moisture levels at >3.5 cm were not significantly depleted. However, there was evidence of soil drying at <3.5 cm. Soil temperature (at 10 cm) at the time of measurement was most strongly correlated to rates of soil respiration. Temporal variability and treatment effects (harvesting and slash piling) played a minor role in explaining soil respiration rates when variations in soil respiration were adjusted for 10-cm soil temperature,. Soil moisture levels (3.5-9.5 cm depth), which did not vary widely, also played a minor role in explaining soil respiration rates.Key words: Clearcut, Abies balsamea, Picea marinara, carbon dioxide, greenhouse gas
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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 | 0.001 | 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) | 0.001 | 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".