Natural disturbance and old-forest management in the Alberta Foothills
Bibliographic record
Abstract
There is no widely accepted definition of old growth for west central Alberta. The Foothills Model Forest used tree species composition and time since major disturbance to more broadly define old forest and a stochastic model to project levels of old forest across a landscape. Historically, the simulated "natural" forest landscape was, at any one time, mostly covered by young forest due to active fires. Areas of mature and old forest were, and likely always have been, in the minority. There were even rare times historically when virtually no old forest existed over vast landscapes, and what little did persist occurred in small, isolated patches. The single greatest human influence on old growth in the Alberta Foothills appears to have been successful fire control, which has produced forests today that are on average older than would be expected under natural conditions. Managers of both protected areas and working forests are implementing or developing strategies to restore forests to more natural conditions, and at the same time managing old forest to ensure that it remains a part of current and future forest landscapes. We describe an old-forest analysis and strategy recently incorporated into a new Forest Management Plan for the Weldwood of Canada Limited Forest Management Area. Traditional attitudes toward old forest and its role in highly dynamic landscapes are being revisited on the path to a consistent and broadly supported old-forest strategy. Key words: old growth, management, natural disturbance, Alberta
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".