Evolutionary and ecological correlates of early seedling morphology in East African trees and shrubs
Bibliographic record
Abstract
Seed size and cotyledon morphology are two key juvenile traits that have evolved in response to changes in plant species life-history strategies and habitat associations. Correlations of these traits with each other and with other juvenile traits were examined for 70 species of trees and shrubs in Kibale National Park, Uganda. Although species with photosynthetic cotyledons were more abundant than in other tropical floras, both univariate and multivariate analyses supported trait associations expected from the literature. Trait values varied continuously across species, yet mean trait values differed significantly among habitat association types. Species with large seeds, large seedlings, thick storage cotyledons, slow germination, large-stature adults, and dispersal by large animals were common in forest and gap habitats. An opposite suite of traits was common in open habitats (grassland and edge). Analyses incorporating phylogeny (independent contrasts and omnibus tests) confirmed that these suites of traits showed correlated evolution. Cotyledon functional morphology yielded a strong phylogenetic signal, while seed mass was labile. Nevertheless, contingent change tests found that evolutionary change from photosynthetic to reserve cotyledons was more likely when disperser and perhaps seed size of ancestral species were already large, suggesting a strong interdependency among these traits.
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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 | 0.001 | 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".