Predicting the effects of woodcutting and moose browsing on forest development in Gros Morne National Park, Newfoundland, Canada
Bibliographic record
Abstract
Long-term scenario analysis was used to predict the effects of domestic harvesting and moose (Alces alces) browsing on forest growing stock, species composition, and age-class distribution for two groups of managed forest blocks dominated by balsam fir (Abies balsamea [L.] Mill.) in Gros Morne National Park (GMNP), western Newfoundland. Four scenarios were examined. The first scenario assumed no timber harvesting and light moose browsing. Transition rules applied to this scenario came from neighbouring industrial forests, where moose populations are regulated by hunting. The other test scenarios use GMNP-specific transition rules to address increased moose browsing in the park, where hunting has been prohibitedsince the park’s inception in 1973. One of the three tested scenarios was also given a “no timber harvest treatment” so that the effects of moose browsing on park forests may be quantified by comparison with the first scenario. The two remaining test scenarios were designed to address compound effects of timber harvesting and moose browsing within the park, each representingan alternative management sce- nario currently being implemented in GMNP. For both harvest scenarios, the overall achievable wood volume was found to be at least five orders of magnitude lower than growing stock, thus providing sufficient volume for the ongoing domestic wood- cutting program (1973-2060) in the park. The proposed levels of woodcutting were predicted to have little impact on forest growing stock and old-growth forest after 160 years of management, but not on maintaining white birch (Betula papyrifera Marsh.), which is already in low numbers. In contrast, moose browsing, although it was predicted to have little effect on age-class distribution, was estimated to cause a 12% to 32% reduction in growing stock over a 160-year planning horizon, depending on the scenario. This was characterized by a 47% to 50% reduction in growing stock of balsam fir and a 50% to 87% reduction in white birch, and a commensurate expansion in low-density black spruce (Picea mariana [Mill.] BSP) and grassland cover. Key words: balsam fir, black spruce, domestic harvest, grassland, scenario analysis, white birch
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".