Driving factors of conifer regeneration dynamics in eastern Canadian boreal old-growth forests
Bibliographic record
Abstract
Abstract Old-growth forests play a major role in conserving biodiversity, protecting water resources, sequestrating carbon, and these forests are indispensable resources for indigenous societies. To preserve the ecosystem services provided by these boreal ecosystems, it becomes necessary to develop novel silvicultural practices capable of emulating the natural dynamics and structural attributes of old-growth forests. The success of these forest management strategies depends on developing an accurate understanding of natural regeneration dynamics. Our goal was therefore to identify the main patterns and the drivers involved in the regeneration dynamics of old-growth forests, placing our focus on boreal stands dominated by black spruce ( Picea mariana (L.) Mill.) and balsam fir ( Balsam fir (L.) Mill.) in eastern Canada. We sampled 71 stands in a 2200 km 2 study area located within Quebec’s boreal region. For each stand, we noted tree regeneration (seedlings and saplings), structural attributes (diameter distribution, deadwood volume, etc.), and abiotic (topography and soil) factors. We observed that secondary disturbance regimes and topographic constraints were the main drivers of balsam fir and black spruce regeneration. Furthermore, the regeneration dynamics of black spruce appeared more complex than those of balsam fir. We observed distinct phases of seedling production first developing within the understory, then seedling growth when gaps opened in the canopy, followed by progressive canopy closure. Seedling density, rather than the sapling density, had a major role in explaining the ability of black spruce to fill the canopy following a secondary disturbance. The density of balsam fir seedlings and saplings was also linked to the abundance of balsam fir trees at the stand level. This research helps explain the complexity of old-growth forest dynamics where many ecological factors interact at multiple temporal and spatial scales. This study also improves our understanding of ecological processes within native old-growth forests and identifies the key factors to consider when ensuring the sustainable management of old-growth boreal stands.
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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 | 0.001 |
| 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 | 0.001 | 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".