Ecological impact of a microburst windstorm in a northern hardwood forest
Bibliographic record
Abstract
We quantified damage by a microburst windstorm to a northern hardwood forest (Hubbard Brook Experimental Forest, New Hampshire). These storms may be important in regulating the structure and composition of forests of the northeastern United States, but few studies of damage patterns from microbursts have been reported. In the 600 ha area most heavily impacted by the microburst at Hubbard Brook, 4.6% of the canopy was removed. Although most disturbances were small (<200 m2), much (22%) of the area damaged by the storm was associated with one 5.2 ha blowdown within which 76% of the trees suffered severe damage. Roughly one-half of the damaged trees were uprooted and one-quarter were snapped off, with few differences among tree species. The remaining trees in the blowdown either avoided damage or suffered less severe damage (i.e., leaning but not snapped or uprooted). Regeneration of shade-intolerant (pin cherry (Prunus pensylvanica L. f.)) and mid-tolerant (yellow birch (Betula alleghaniensis Britt.), red maple (Acer rubrum L.)) trees was present in the large canopy gaps. While recruitment opportunities in these large gaps may be important for maintaining populations of pioneer species, the limited spatial extent of microbursts suggests that they play a minor role in the overall dynamics of the northeastern forest.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".