Ice storm effects on the canopy structure of a northern hardwood forest after 8 years
Bibliographic record
Abstract
Ice storms can cause severe damage to forest canopies, resulting in differential mortality among tree species and size classes and leading to long-lasting changes in the vertical structure and composition of the forest. An intense ice storm in 1998 damaged large areas of the northern hardwood forest, including much of the Hubbard Brook Experimental Forest, New Hampshire (USA). Following up on detailed poststorm assessments, we measured changes in the vertical structure of the forest canopy 8 years poststorm. We focused on how the presence of disease-induced advance regeneration of American beech ( Fagus grandifolia Ehrh.) has affected canopy structure in the recovering forest. We measured foliage-height profiles using a point-quadrat approach and a pole-mounted leaf area index (LAI) sensor. Although the total LAIs of damaged and undamaged areas were similar, areas damaged in 1998 showed an increased proportion of total leaf area between 6 and 10 m above the ground. The foliage at this height is largely (54%) beech. To the extent that this heavily beech-dominated understory layer suppresses regeneration of other species, these findings suggest that rare disturbances of mature northern hardwood forests affected by beech bark disease will increase the importance of damage-prone and economically marginal beech.
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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 | 0.000 | 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 | 0.000 | 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".