Microsite differentiation among conifer species during seedling establishment at alpine treeline
Bibliographic record
Abstract
:Tree establishment is a potentially important factor affecting tree populations in alpine-treeline ecotones. Patterns of seedling establishment of Abies lasiocarpa, Pinus albicaulis, and Picea engelmannii were evaluated relative to neighbouring trees and herbs over two years and three treelines of the Rocky Mountains, USA. The greatest mortality rates were observed in seedlings that had just emerged from seed and were in their first year of growth and in seedlings that had the least amount of cover provided by trees or other landscape features that block exposure to the sky. Although herb cover promoted survivorship in microsites that were not near trees, no seedlings were detected at or above the upper limit of the treeline ecotone. Microsite tree cover was greatest for A. lasiocarpa and least for P. albicaulis seedlings, which matches predictions based on their relative photosynthetic tolerances to the bright sunlight and frequent frost that occur in exposed microsites. Interspecific differences in seedling requirements for neighbouring plant cover likely contribute to the apparent coexistence and possible interdependency of these conifers along a continuum of colonization and succession within treelines.
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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".