Degradation of Boreal Forests by Nonnative Herbivores in Newfoundland's National Parks: Recommendations for Ecosystem Restoration
Bibliographic record
Abstract
For land management agencies such as Parks Canada that are tasked with maintaining the ecological integrity of protected, natural landscapes, dealing with the impacts of non-indigenous species on forest succession is a serious management concern. In both Terra Nova and Gros Morne National Parks (island of Newfoundland, Canada), the cumulative impacts of non-native species are negatively affecting the capacity of a dominant conifer, balsam fir (Abies balsamea), to regenerate following canopy disturbance by forest insects. Early development of an understory fir layer is compromised by heavy predation on female cones by red squirrels (Tamiasciurus hudsonicus), and post-dispersal seed and seedling predation by non-native rodents and slugs. Taller saplings are then subjected to heavy browsing from non-native moose (Alces alces) so that recruitment to reproductive-aged trees is largely inhibited. An indirect effect of the long-term removal of understory fir is that seedbeds are shifting from optimal feathermoss types towards seedbeds dominated by competing grasses and non-native plants, thus reducing potential germination of balsam fir. We provide evidence that these changes to forest composition and structure are occurring at large spatial scales across both protected and non-protected landscapes. Finally, we offer management recommendations including sustained reductions of moose numbers and the supplemental planting of fir where understory densities are exceptionally low and seedbed degradation has occurred.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".