The effects of cording, timber load and soil gravel content on soil compaction during timber harvesting on moist soils
Bibliographic record
Abstract
Summary Timber harvesting with heavy machinery can cause long-lasting compaction of forest soils, adversely affecting soil processes such as infiltration and respiration that are fundamental to forest health. This study examined the effectiveness of corduroying as a means of reducing soil compaction on log extraction tracks during timber harvesting under moist soil conditions in the forests of south-western Western Australia. The effects of the weight of logs removed from the stand, soil gravel content and initial bulk density, were also considered. Timber harvesting under moist soil conditions lead to significant compaction of surface soil on primary and secondary extraction tracks. This compaction was significantly related to four factors: timber load, initial soil bulk density and gravel content, and the use of cording. Compaction increased as the total load of timber hauled over the tracks increased. Soils with a high initial bulk density were less compacted during timber harvesting than soils with a low initial bulk density. On soils with initial bulk densities greater than about 0.55 g cm−3, compaction decreased as gravel content of the soil increased. Cording also significantly reduced soil compaction, but this reduction was small and may not justify the cost or the associated negative environmental impacts of routinely using corduroying while harvesting timber on moist soil. While reducing the load of timber hauled over an extraction track reduces soil compaction, this does not provide a practical solution for reducing soil damage in timber harvesting. Rather than dispersing traffic across many extraction tracks to reduce the load on individual tracks, the impact of soil compaction is best minimised by focusing all traffic onto as few tracks as possible; thus minimising the area of forest soil that is compacted by harvesting machinery. In addition, reusing compacted extraction tracks that remain from any previous harvesting is one of the most effective means of reducing the impact of timber harvesting on forest soils.
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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 | 0.000 | 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) | 0.001 | 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".