Old growth in the boreal forest: A dynamic perspective at the stand and landscape level
Bibliographic record
Abstract
Old-growth forests have been identified as a potentially important stage of stand development for maintaining biodiversity in the landscape, yet they have also been targeted by the forest industry in their drive to regulate the forest. We will attempt to propose a definition of old growth, applicable throughout the North American boreal forest, that takes into account the dynamic nature of forest development and that could be useful for management and conservation purposes. We define the start of the old-growth stage as occurring when the initial post-disturbance cohort begins dying off, concurrent with understorey stem recruitment into the canopy. We propose that species longevity and the regional fire cycle can be used to assess the extent of this phase in different regions. Using published data on fire history, we show that the amount of old growth expected to occur in western and central Canada is less than in eastern Canada, where most stands (in area) escape fire for periods longer than that necessary to incur substantial mortality of the initial cohort. At the stand level, we show that the old-growth stage is characterized by small-scale disturbances that engender gap dynamics. Until recently, this process had not been studied in the boreal forest. The old-growth index we present suggests that the relationship between time since the last major disturbance and old-growth status varies most in areas that have not been disturbed for long periods. Both management and conservation strategies have to take into account that old-growth forests are dynamic. To be effective, reserves should contain all stages of development and should be sufficiently large to encompass rare but large disturbances. The abundance of old growth in many boreal regions of North America also suggests that forest management strategies other than even-aged, fully regulated systems have to be developed. Key words: old growth, old-growth index, boreal forest, conservation, forest management, stand development.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".