Interspecific variation in susceptibility to windthrow as a function of tree size and storm severity for northern temperate tree species
Why this work is in the frame
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Bibliographic record
Abstract
Studies of wind disturbance regimes have been hampered by the lack of methods to quantify variation in both storm severity and the responses of tree species to winds of varying intensity. In this paper, we report the development of a new, empirical method of simultaneously estimating both local storm severity and the parameters of functions that define species-specific variation in susceptibility to windthrow as a function of storm severity and tree size. We test the method using data collected following a storm that struck the western Adirondack Mountains of New York in 1995. For intermediate-sized stems (e.g., 40 cm DBH), black cherry (Prunus serotina Ehrh.) and red spruce (Picea rubens Sarg.) showed the highest rates of windthrow across virtually all levels of storm severity, while yellow birch (Betula alleghaniensis Britt.) and sugar maple (Acer saccharum Marsh.) had the lowest rates of windthrow. For much of the range of storm severity, the probability of windthrow for the most susceptible species was at least twice as high as for the least susceptible species. Three of the species, yellow birch, red spruce, and beech (Fagus grandifolia Ehrh.), had significantly lower probability of windthrow at a given storm severity in old-growth stands than in second-growth stands. Our results suggest that the distinctive abundance of these three species in old-growth forests of the Adirondacks is due, at least in part, to their ability to survive the intermediate-scale disturbance events that appear to dominate the natural disturbance regime in this region.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 it