Leaf and root traits are partially coordinated but they show contrasting multi-trait-based community trait dispersion patterns in a subtropical forest
Bibliographic record
Abstract
Abstract The ecology of plant species relies on the synchronous functioning of leaves and roots, but few studies have simultaneously examined the community trait dispersion (CTD) patterns of both organs. We measured 16 analogous leaf and root traits on 44 co-occurring woody species in a subtropical forest in southern China, aiming to examine whether leaf and root traits were coordinated, organized into parallel trait axes, exhibited similar CTD, and displayed consistent responses in CTD and community-weighted means of (CWM) traits over environmental gradients. While the first axes of leaf and root trait variation similarly exhibited a fast–slow continuum, leaf traits covered a secondary “carbon economics” axis, contrasting to root traits depicting a collaboration axis reflecting species’ mycorrhizal dependency. Analogous leaf and root chemical traits were generally coordinated but less so for morphological traits. At the community level, changes in the CWM of the first axes were generally consistent among organs with more conservative traits found as increasing elevation but not for the second axis. While root traits became thinner and more conservative as soil phosphorus concentration decreased, leaf traits rarely varied. When different trait axes were combined, leaf traits were overdispersed but tended to converge with increased elevation and soil potassium and phosphorus levels, whereas root traits were clustered but tended to diverge along the same gradients. Our study highlights fine filtering of different suites of traits above- and belowground, which in turn might reduce overall niche overlap among species and promote coexistence with diverse functional designs.
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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 | 0.001 | 0.001 |
| 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 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".