Soil properties influencing compactability of forest soils in British Columbia
Bibliographic record
Abstract
The widespread use of heavy machinery during harvesting and site preparation in timber plantations in British Columbia (BC) has led to concerns that compaction causes a reduction in long-term soil productivity. Impacts of properties such as total C, water content, and texture on compactability of forest soils in BC were assessed. Two compactability indices were used: maximum bulk density (MBD) and susceptibility to compaction (SC) determined by the standard Proctor test. Soil samples were collected from 16 sites throughout BC covering a wide range of biogeoclimatic zones. Soils varied in texture (12 to 87% sand, 9 to 76% silt, and 2 to 53% clay) and organic matter content (18 to 76 g kg-1 total C). A strong negative correlation was observed between MBD and gravimetric water content at which MBD was achieved (WMBD) and between MBD and total C. Similarly, WMBD and total C had strong effects on SC. The estimation of either MBD or SC values was not substantially improved by including texture parameters to the regression equations in addition to the total C. The implication of the relationships observed in this study is that increases in soil organic matter reduce the risk of compactability, which is particularly important for forest soils where compaction is generally not corrected by implements after tree planting. The information is also useful for assessing the extent of compaction on soils affected by machine traffic. Key words: Soil compaction, Susceptibility to compaction, maximum bulk density, Proctor test, total carbon
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".