Snowpack recovery in regenerating coastal British Columbia clearcuts
Bibliographic record
Abstract
A study was undertaken to define curves of snowpack recovery for coastal B.C. forests. The study was conducted using repeated snow course sampling techniques under regenerating stands with a range of canopy heights, and old growth. Measurements were made over five seasons from 1992-1993 to 1996-1997. For each season, recovery factors due to both peak accumulation and post-peak ablation rate were calculated for the regenerating stands. These factors were calculated using linear interpolation between extremes defined by the peak accumulation or ablation rate of old growth and clear-cut equivalent plots. An asymptotic exponential model was found to provide a reasonable fit to the data of recovery as a function of either canopy height or canopy density. The results suggest that there is a hydrologic recovery threshold at a level where the tallest trees in the stand are at a height roughly equal to the mean peak snow depth for open sites. Recovery proceeds rapidly; at a height of 4 m or canopy density of 20%, expected recovery is about 50%. At a height of 8 m, or a canopy density of 45%, expected recovery is about 75%, and by the time the trees have reached a height of 20 m, or more than 95% canopy density, the stand approaches full recovery. These results demonstrate how clear-cut harvesting and subsequent regeneration affect snow accumulation and ablation at the site level, but do not address the important issue of how those changes affect streamflow at the watershed scale.
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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 | 0.001 | 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".