Factors limiting the recruitment of Quercus schottkyana, a dominant evergreen oak in SW China
Bibliographic record
Abstract
Quercus schottkyana is a dominant species of oak in the Asian evergreen broad-leaved forests in southwestern China but seedlings are uncommon and recruitment is rare. Annual acorn production by Q. schottkyana is variable and the acorns are exposed to a series of mortality risks. Understanding the factors that limit recruitment of the oak requires knowledge of the oak's life cycle from acorn production to germination and seedling establishment. In this study, we first tested the effects of acorn density on establishment of seedlings by placing batches of acorns at different densities throughout the study area. Second, we tested the effects of herbivores on seedling survival by erecting fences around both natural and transplanted seedling populations. Our results show that even though the rate of seedling establishment increases as acorn density increases (for 32–8000 acorns∙m−2), survival rates of seedlings in the field were generally low (0–0.6%). We show that seedling recruitment of Q. schottkyana is mainly limited to the acorn stage where 88% of the acorns died from the combined effects of desiccation and predation by weevils (Curculio) and bark beetles (Coccotrypes sp.). Herbivory results in the death of some seedlings and consequently also affects the recruitment of seedlings of Q. schottkyana.
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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 | 0.001 | 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 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".