Soil compaction associated with cut-to-length and whole-tree harvesting of a coniferous forest
Bibliographic record
Abstract
The degree and extent of soil compaction, which may reduce productivity of forest soils, is believed to vary by the type of harvesting system, and a field-based study was conducted to compare soil compaction from cut-to-length (CTL) and whole-tree (WT) harvesting operations. The CTL harvesting system used less area to transport logs to the landings than did the WT harvesting system (19%–20% vs. 24%–25%). At high soil moisture levels (25%–30%), both CTL and WT harvestings caused a significant increase of soil resistance to penetration (SRP) and bulk density (BD) in the track compared with the undisturbed area (p < 0.05). In the center of trails, however, only WT harvesting resulted in a significant increase of SRP and BD compared with the undisturbed area (p < 0.05). Slash covered 69% of the forwarding trail area in the CTL harvesting units; 37% was covered by heavy slash (40 kg·m–2) while 32% was covered by light slash (7.3 kg·m–2). Heavy slash was more effective in reducing soil compaction in the CTL units (p < 0.05). Prediction models were developed that can be used to estimate percent increases in SRP and BD over undisturbed areas for both CTL and WT harvesting systems.
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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 | 0.000 | 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".