Size- and environment-driven seedling survival and growth are mediated by leaf functional traits
Bibliographic record
Abstract
Ecologists usually find that plant demography (e.g. survival and growth) changes along with plant size and environmental gradients, which suggests the effects of ontogeny-related processes and abiotic filtering. However, the role of functional traits underlying the size- and environment-demography relationships is usually overlooked. By measuring individual-level leaf traits of more than 2700 seedlings in a temperate forest, we evaluated how seedling traits mediated the size- and environment-demography relationships. We found leaves were larger for taller seedlings; leaf economics traits were more conservative in taller seedlings and under high-light and low-elevation conditions. Structural equation modelling showed that a higher survival probability for taller seedlings was indirectly driven by their larger leaf area. Although taller seedlings had lower growth rates, larger and more resource-conservative leaves could promote the growth of these tall seedlings. Environmental variables did not influence seedling survival and growth directly but did influence growth indirectly by mediating trait variation. Finally, species-specific variation in traits along with size and environments was associated with the species-specific variation in seedling survival and growth. Our study suggests that not only plant ontogeny- and environment-related ecological processes, but functional traits are also important intermediary agents underlying plant size- and environment-demography relationships.
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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 | 0.001 |
| 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".