Effects of sand burial and overstory tree age on seedling establishment in coastal Pinus thunbergii forests in the northern Shandong Peninsula, China
Bibliographic record
Abstract
Coastal Pinus thunbergii (Japanese black pine) forests in the northern Shandong Peninsula of China recently experienced widespread natural regeneration failure. This study identifies critical factors that affect natural regeneration of P. thunbergii. Seeds from trees of various ages (13–32 years) were used to investigate the effects of age and burial depth in sand on germination and seedling establishment. Results show that seed density in 2–5 cm soil decreased with increased distance from the shoreline. Sand burial decreased seed germination but did not affect the relative growth rate of seedlings at depths from 0.5 to 3 cm. Germination, leaf mass ratio, and relative growth rates were higher with seedlings originating from older trees, all of which enhanced seedling resistance to sand burial. Tree age and seed burial were found to be determining factors for natural regeneration of the coastal P. thunbergii forest. Silvicultural treatments that promote quality of seed sources and mitigation of sand burial can be used in the future to improve the regeneration of these coastal forests.
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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) | 0.000 | 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".