Seed size and recruitment patterns in a gradient from grassland to forest
Bibliographic record
Abstract
Seedlings germinating from large seeds are known to endure hazards such as shading, competition, and litter coverage better than seedlings germinating from small seeds. However, few studies have assessed the relationships between seed size and recruitment comparing plant communities with different structures in order to establish the conditions under which a seed-size advantage prevails. Here, seeds from 20 species varying in seed size from 0.05 to 17.8 mg were sown in 6 different vegetation types, representing a gradient from open grassland to closed canopy coniferous forest. We hypothesized that the effect of seed size on recruitment is generally positive, but that there is a stronger positive effect of seed size in closed than in open communities. Our results provided only limited support for this hypothesis. Firstly, the results varied between years, suggesting that any seed size advantage may depend on factors varying on an annual basis. Secondly, although there were trends of significantly positive relationships between seed size and seedling emergence, seedling survival, and recruitment success, particularly in relatively more closed vegetation types, the strongest positive effects of seed size were found in intermediate (semi-open) habitats along the gradient. We conclude that the filtering of species into the investigated communities is only weakly related to seed size, and that several factors other than canopy probably influence the link between seed size and recruitment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".