Wind and snow damage nine years following four harvest treatments in a subalpine fir – Engelmann spruce forest at Sicamous Creek in southern interior British Columbia, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We used transect surveys at a large-scale experimental site at Sicamous Creek, B.C. to measure the effects of five treatments on wind and snow damage in an old subalpine fir – Engelmann spruce forest: 10-ha clearcuts, arrays of 1-ha patch cuts, arrays of 0.1-ha patch cuts, individual-tree selection cuts and uncut controls. We also examined edge effects and conditions predisposing trees to damage. Transects were surveyed in 1997, 1999 and 2003 (2.7, 4.7 and 8.7 years postharvest). The increase in wind damage in the four harvested treatments compared to the uncut controls observed after 2.7 years was no longer evident following a snow damage event in the winter of 1998–1999, which was most severe in the uncut controls and leave strips. The damage recorded from this event was predominantly stem snapping rather than uprooting. Subsequent damage was low in all treatments, returning to the level first recorded in the uncut controls. Overall, after 8.7 years, the treatment differences were not statistically significant but the lowest average rates of damage were observed in the 0.1-ha patch cut arrays. The highest damage rates overall were observed within 10 m of the N and E edges of the 10-ha clearcuts. Damage rates in Engelmann spruce continued to be lower than rates for subalpine fir. Stem snapping, caused by some combination of snow loading and wind, is an underreported but widespread disturbance in these stands. Key words: ESSF forest, wind damage, snow damage, snapping, uprooting, subalpine fir (Abies lasiocarpa [Hook] Nutt.), Engelmann spruce (Picea engelmannii Parry ex Engelm.), silvicultural systems, Sicamous Creek
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it