Hailstorm damage promotes aspen invasion into grassland
Bibliographic record
Abstract
Global warming is widely thought to promote the dominance of grasslands over woody vegetation, and shift the location of ecotones. In contrast, forest vegetation along the northern edge of the North American Great Plains has migrated southward over the past century into areas dominated by native grassland. Because climate change is also predicted to increase storm frequency and intensity, we quantified the impacts of an intense hailstorm on woody and herbaceous species in native grassland in the northern Great Plains of North America. The hailstorm disturbance killed or damaged mature stems of the dominant tree, aspen ( Populus tremuloides Michx.), but damaged aspen stands subsequently invaded ca. 10 m into neighbouring grassland. Damaged aspen stands also produced up to 20-fold more new stems having 67-fold higher total biomass compared with relatively undisturbed stands. Grasses and lichens suffered much higher rates of biomass removal (60%–76%) than did shrubs (6%–8%) immediately following the storm. The disturbance-mediated recruitment of clonal woody plants, and the unexpected sensitivity of grasses and lichens to this disturbance, may contribute to the counterintuitive expansion of trees into grasslands under a regime of increased storm frequency that is not predicted by simple ecosystem responses to warming.
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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".