Investigating Fire as a Silvicultural Tool for Regeneration of Mountain Pine Beetle-killed Serotinous Pine of Northern Alberta
Bibliographic record
Abstract
Serotinous pine forests in Western Canada are threatened by a record-breaking mountain pine beetle (Dendroctonus ponderosae; MPB) outbreak - the largest recorded in Western North America. Forest managers are concerned with whether these closed-cone MPB-killed forests will successfully regenerate. The study indicates fire is required for successful regeneration and suggests that of the two limiting factors of serotinous pine regeneration, the differences are likely accounted for by cone opening. It was evident in the data, however, that the objective of duff removal is not as greatly achieved after surface fire and, quite likely linked, MPB-killed stands will likely regenerate most successfully after a continuous crown fire. Due to the variable nature of fire, however, it is difficult to provide a clear recommendation on which type of fire would yield the greatest regeneration. This study is the first to clearly indicate there is active moisture exchange of serotinous lodgepole pine cones from both live and MPB-killed trees. The moisture exchange rate was similar among cones of live and MPB-killed trees, but it takes more time to open cones from MPB-killed trees. The results suggested that cone moisture is not the sole driving factor determining the time taken to open serotinous cones, but the mortality condition and age also play a role in the process. This indicates that the cones from MPB-killed trees might have wider window of survival after fire.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".