Coordination of leaf and stem traits in 25 species of Fagaceae from three biomes of East Asia
Bibliographic record
Abstract
It has been debated whether leaf and stem economics spectra are coordinated across species, because previous studies have provided contradictory results. These studies have been restricted to single biomes, and we hypothesize that climate seasonality may determine the strength of coordination between leaf and stem trait combinations. Herein, using 25 Fagaceae species from East Asia, we investigated the coordination of 16 leaf traits and 5 stem traits across and within three biomes (cool temperate, warm temperate, and tropical forests). The traits were chosen to reflect multiple aspects of plant adaptive strategies, such as water, carbon, and nutrient use. The leaf and stem traits of species that reflect resource-use strategies for different resources were functionally coordinated, forming a single axis of trait variation across biomes. This axis represents the trade-off between fast and slow resource-use strategies. We found the trend that the coordination between leaf and stem traits was the strongest in cool temperate forests after removing two Fagus species, followed by warm temperate forests, but was not observed in tropical forests. Our results support the proposed model that plants vary from slow to fast resource exploitation, using closely related species, and suggest that temperature modulates the coordination of leaf and stem economics spectra.
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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".