The variability of root cohesion as an influence on shallow landslide susceptibility in the Oregon Coast Range
Bibliographic record
Abstract
Decades of quantitative measurement indicate that roots can mechanically reinforce shallow soils in forested landscapes. Forests, however, have variations in vegetation species and age which can dominate the local stability of landslide-initiation sites. To assess the influence of this variability on root cohesion we examined scarps of landslides triggered during large storms in February and November of 1996 in the Oregon Coast Range and hand-dug soil pits on stable ground. At 41 sites we estimated the cohesive reinforcement to soil due to roots by determining the tensile strength, species, depth, orientation, relative health, and the density of roots [Formula: see text]1 mm in diameter within a measured soil area. We found that median lateral root cohesion ranges from 6.823.2 kPa in industrial forests with significant understory and deciduous vegetation to 25.694.3 kPa in natural forests dominated by coniferous vegetation. Lateral root cohesion in clearcuts is uniformly [Formula: see text]10 kPa. Some 100-year-old industrial forests have species compositions, lateral root cohesion, and root diameters that more closely resemble 10-year-old clearcuts than natural forests. As such, the influence of root cohesion variability on landslide susceptibility cannot be determined solely from broad age classifications or extrapolated from the presence of one species of vegetation. Furthermore, the anthropogenic disturbance legacy modifies root cohesion for at least a century and should be considered when comparing contemporary landslide rates from industrial forests with geologic background rates.Key words: root strength, cohesion, landslide, debris flow, land use, anthropogenic disturbance.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".