Structure and composition of forest edges created by a spruce budworm outbreak and maintained by moose browsing in Cape Breton Highlands National Park
Bibliographic record
Abstract
Structure and composition of forest edges created by a spruce budworm outbreak and maintained by moose browsing in Cape Breton Highlands National Park By Caroline FranklinNatural forest edges created by a severe spruce budworm outbreak in Cape Breton Highlands National Park, Nova Scotia, Canada, have been maintained three decades postdisturbance by moose browsing.My overall research objective was to determine the direct and indirect effects of edge creation on vegetation structure and composition.Trees, deadwood, and understorey plants were sampled along 120 m transects perpendicular to six forest edges.The spruce budworm-induced forest edges were characterized by narrow transition zones where canopy cover, stem density, and structural diversity were intermediate between the disturbed area and forest.Severe moose browsing appears to be preventing sapling growth and altering species composition, particularly on the insect disturbed side of the edge.If moose continue to maintain the forest edge, contrasts in vegetation structure and composition between the severely browsed disturbed area and adjacent intact forest could increase and ultimately alter forest edge function.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".