Patterns of initial versus delayed regeneration of white spruce in boreal mixedwood succession
Bibliographic record
Abstract
The timing of white spruce regeneration in aspen (Populus tremuloides Michx.) white spruce (Picea glauca (Moench) Voss) boreal mixedwood stands is an important factor in stand development. We examined boreal mixedwood stands representing a 59-year period of time since fire and determined (1) whether and when a delayed regeneration period of white spruce occurred, (2) whether the relative abundance of initial (<20 years) versus delayed (≥20 years postfire) regeneration is related to seed availability at the time of the fire, and (3) what are the important regeneration substrates for initial versus delayed regeneration. Initial regeneration occurred primarily on mineral soil or humus, while delayed regeneration established primarily on logs and peaked 3844 years after fire. Of the 20 stands investigated, seven were dominated by initial regeneration, six were dominated by delayed regeneration, and seven were even mixtures of both. The dominance of a site by initial or delayed regeneration could not be simply explained by burn timing relative to mast years or distance to seed source; our results suggested that fire severity and the competitive influence of initial regeneration on delayed regeneration were important at fine scales. Based on our results we describe several possible postfire successional pathways for boreal mixedwood 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".