Forest disturbance effects on snow and water yield in interior British Columbia
Bibliographic record
Abstract
Long-term studies at Mayson Lake (ML) and Upper Penticton Creek (UPC) in British Columbia's southern interior quantify snow-dominated hydrologic response to natural disturbances and logging. Following natural disturbance at ML, changes in snow accumulation related directly to mountain pine beetle attack were measurable by the fifth year following attack, when canopy transmittance had increased 24% due to needlefall. In year 1, April 1 snow water equivalent (SWE) was 48% higher in the clearcut than in the pine forest. This difference was reduced to 23% by year 8. A 3-year lag in snow response was also observed in a nearby burned stand where SWE was on average 27 and 59% higher in the clearcut than in the burn and forest, respectively. At UPC, April 1 SWE averaged 12% more and 12% less in a low and high elevation clearcut than forest, respectively, and snow disappeared ∼10 days earlier in both clearcuts. Partially as a result of snowmelt synchronization from higher with lower elevations after 50% of the treatment watersheds had been clearcut, April water yield increased and June to July yield decreased. Research results improve evaluation of hydrologic response to forest disturbance, including retention of beetle-killed stands versus salvage logging.
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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) | 0.002 | 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".