Clonal traits outperform foliar traits as predictors of ecosystem function in experimental mesocosms
Bibliographic record
Abstract
Abstract Questions Is productivity linked with clonal traits through their indirect effect on competitive interactions? Are clonal traits better predictors of productivity than foliar traits? Location R ennes, F rance. Methods We used a wide‐scale mesocosm experiment based on several assemblages of species differing in clonal traits, and evaluated if the relationship between biomass production and clonal traits is consistent at different ecological scales. Results Results showed that at the individual level, foliar traits were independent from clonal traits in most studied species. Community specific above‐ground net primary productivity was significantly correlated to community‐aggregated values of clonal and foliar traits. Nevertheless, a stronger relationship with clonal traits was indicated, emphasizing a plant foraging strategy along the horizontal plant plane, which was a determinant of community productivity. An inverse relationship between clonal traits and biomass production was observed at the individual and community levels, which was attributed to modifications in resource acquisition processes resulting from competitive interactions. Conclusions We demonstrated that clonal traits are correlated with productivity at the individual and community scales. These traits were indicators of resource acquisition processes mediated through competitive interactions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".