A spatial and temporal model of root cohesion in forest soils
Bibliographic record
Abstract
Root cohesion is an important parameter governing slope stability in steep forested terrain. Forest harvesting impacts root cohesion, and although the temporal effects have been noted, this dynamic parameter is often assumed to be spatially uniform. A model was developed to simulate the variation in root cohesion on a hillslope resulting from various forest management treatments. The model combines physical data on the horizontal rooting distribution of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. menziesii) together with a temporal relation of root cohesion decay. Harvesting methods examined include clear-cutting, single-tree selection cutting, and strip-cutting. Model outputs are analysed qualitatively for regions of root cohesion minima and quantitatively for the average root cohesion within the simulated hillslope. A selection cutting simulation maintained the highest average root cohesion value, decreasing to only 81% of the preharvest condition. In contrast, the minimum root cohesion following clear-cutting declined to 38% of the preharvest value. Selection and strip-cutting scenarios resulted in smaller areas of reduced root cohesion that were adjacent to areas with high root cohesion. Such partial cutting methods shorten the period of reduced root cohesion following timber harvesting compared with clear-cutting.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".