Seedling emergence and early growth of Chinese fir under different light levels and seed positions: implications for natural regeneration
Bibliographic record
Abstract
Chinese fir, Cunninghamia lanceolata (Lamb.) Hook. (Taxodiaceae), is an evergreen conifer primarily distributed in southern China. This species exhibits very poor natural regeneration, possibly due to low light and a thick litter layer. To improve the understanding of the natural regeneration capacity of Chinese fir, in this study, we conducted a shade house experiment to determine the optimum light requirements and seed positions for seedling emergence and early growth. The experiment involved five light levels (100%, 60%, 40%, 15%, 5% of full sunlight) and four seed positions (1 cm beneath the soil surface without litter, on the soil surface without soil–seed contact, on the soil surface and covered with litter, and 1 cm beneath the soil surface and covered with litter). Seedling emergence was highest at 5%–15% sunlight, whereas seedling height, root length, root mass, stem mass, leaf mass, and total mass were highest at 60% sunlight. For each light level, seed position significantly affected emergence and growth. The above-litter position inhibited seedling emergence and survival, while the below-litter position favored seedling emergence and early growth, particularly under high light levels. Based on these results, to enhance natural regeneration of Chinese fir, we recommend periodical thinning to increase light into the understory after successful seedling emergence. We also recommend sowing seeds deeper into the litter to improve soil contact and moisture conditions.
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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".