Beyond shading: Litter production by neighbors contributes to overyielding in tropical trees
Bibliographic record
Abstract
The influence of biodiversity on ecosystem functioning is now well established. However, our ability to predict the ecological consequences of biodiversity changes remains limited by our poor understanding of the mechanisms underlying biodiversity effects. We disentangled the contributions of light competition and residual neighborhood interactions in a 10‐year‐old biodiversity experiment with tropical trees that display overyielding, i.e., higher community‐level yields in mixtures compared with monocultures. We developed models of individual tree growth that partition the effects of neighboring trees into shading and residual effects assumed to reflect primarily belowground interactions. These models reject the hypothesis that reduced light competition in mixtures is the only mechanism driving overyielding. After factoring out the effects of shading, litter production by neighbors was a far better predictor of tree growth than traditional crowding indices; it contributed to overyielding by producing pairwise interactions that ranged from competitive to facilitative, but which, on average, concentrated competition within species. Consistent with litter‐mediated biodiversity effects, the magnitude of overyielding increased over time. Our results provide evidence for diversity effects extending beyond that of light and reveal the neglected role of litter‐mediated interactions among trees.
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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) | 0.001 | 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 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".