Advance regeneration and trajectories of stand development following the mountain pine beetle outbreak in boreal forests of British Columbia
Bibliographic record
Abstract
A mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak has recently spread into boreal forests, with unknown consequences for this ecosystem. We intensively sampled 12 stands affected by the current outbreak in northern British Columbia to determine the potential of western boreal forests to recover from this novel disturbance. We sampled the species composition, size structure, and spatial distribution (using 5 m × 5 m subplots, 40 per stand) of live and dead trees and used a variety of analyses, including ordinations, to assess potential developmental trajectories of stands. Advance regeneration (stems < 10 m tall) varied greatly in abundance among stands (50–18 280 stems·ha−1). However, most subplots contained at least one individual; only three stands had many empty subplots. We conclude that most stands have enough advance regeneration and residual canopy trees to form a nearly continuous new canopy. Ordinations indicate that species composition will shift substantially and become more divergent among stands. Species of high economic value will remain common, though, and active management will not be necessary in most stands to maintain productive forests. However, this novel disturbance will have very different effects on these forests than the typical fire-disturbance regime and is likely to deflect these forests into new successional trajectories.
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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 | 0.000 |
| 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".