Prescribed Burning to Restore Eastern White Pine Forests of La Mauricie National Park of Canada
Bibliographic record
Abstract
Eastern white pine forests of La Mauricie National Park of Canada have been severely affected by logging and forest fire suppression since the 1850s, and by the exotic white pine blister rust since the beginning of the twentieth century. These alterations have changed the ecological trajectory of eastern white pine ecosystems, which now appear hardly sustainable. Eastern white pine saplings are nearly absent, and balsam fir saplings are strong competitors for space and light. Since 1991, Parks Canada uses prescribed burning for restoring eastern white pine ecosystems. We studied seven pine stands in which prescribed burning was applied and compared them with nine unburned stands. Over 63% of balsam fir saplings were killed by prescribed burning, thus eliminating a significant part of the competition to eastern white pine seedlings. These were four times more abundant in burned than in unburned sites (21,333 vs. 5178 seedlings/ha). In the short term, the eastern white pine regeneration objectives established by Parks Canada have been achieved. Pine seedlings growth is slow, and they should be monitored regularly to ensure long-term success of this restoration programme. If necessary, it might be helpful to increase light penetration by girdling mature balsam firs or spruces.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.025 | 0.026 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.007 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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; both teacher heads agree on what is shown here.
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".