Long-term stand dynamics of the boreal mixed-wood forests of west-central Manitoba
Bibliographic record
Abstract
To understand the temporal dynamics of a forest, long-term direct observations are required. My study examined the long-term persistence of trembling aspen (Populus tremuloides Michx) and white spruce (Picea glauca (Moench) Voss) in the boreal mixed-wood forests of Riding Mountain National Park. A set of 266, disturbance-free, permanent sample plots were established in 1947 (stand age = 120 years) and followed through time for 55 years. My results indicate that although the density and basal areas of aspen do decline over the 55-year period, a successful regeneration and establishment occurs around 140 years. The long-term persistence of aspen is a result of clonal reproduction following the canopy breakup beginning around 130 years or earlier. This implies that the long-term persistence of both aspen and spruce occur and the expected succession to softwood dominance does not occur.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".