Linking radial growth patterns and moderate‐severity disturbance dynamics in boreal old‐growth forests driven by recurrent insect outbreaks: A tale of opportunities, successes, and failures
Bibliographic record
Abstract
Abstract In boreal landscapes, emphasis is currently placed on close‐to‐nature management strategies, which aim to maintain the biodiversity and ecosystem services related to old‐growth forests. The success of these strategies, however, depends on an accurate understanding of the dynamics within these forests. While moderate‐severity disturbances have recently been recognized as important drivers of boreal forests, little is known about their effects on stand structure and growth. This study therefore aimed to reconstruct the disturbance and postdisturbance dynamics in boreal old‐growth forests that are driven by recurrent moderate‐severity disturbances. We studied eight primary old‐growth forests in Québec, Canada, that have recorded recurrent and moderately severe spruce budworm (Choristoneura fumiferana [Clem.]) outbreaks over the 20th century. We applied an innovative dendrochronological approach based on the combined study of growth patterns and releases to reconstruct stand disturbance and postdisturbance dynamics. We identified nine growth patterns; they represented trees differing in age, size, and canopy layer. These patterns highlighted the ability of suppressed trees to rapidly fill gaps created by moderate‐severity disturbances through a single and significant increase in radial growth and height. Trees that are unable to attain the canopy following the disturbance tend to remain in the lower canopy layers, even if subsequent disturbances create new gaps. This combination of a low stand height typical of boreal forests, periodic disturbances, and rapid canopy closure often resulted in stands constituted mainly of dominant and codominant trees, similar to even‐aged forests. Overall, this study underscored the resistance of boreal old‐growth forests owing to their capacity to withstand repeated moderate‐severity disturbances. Moreover, the combined study of growth patterns and growth release demonstrated the efficacy of such an approach for improving the understanding of the fine‐scale dynamics of natural forests. The results of this research will thus help develop silvicultural practices that approximate the moderate‐severity disturbance dynamics observed in primary and old‐growth boreal forests.
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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 | 0.000 | 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".