Biodiversity enhances individual performance but does not affect survivorship in tropical trees
Bibliographic record
Abstract
We developed an analytical method that quantifies the relative contributions of mortality and individual growth to ecosystem function and analysed the results from the first biodiversity experiment conducted in a tropical tree plantation. In Sardinilla, central Panama, over 5000 tree seedlings were planted in monoculture and mixed-species plots. After 5 years of growth, mixed-species plots yielded, on average, 30-58% higher summed tree basal area than did monocultures. Simulation models revealed that the increased yield of mixed-species plots was due mostly to enhancement of individual tree growth. Although c. 1500 trees died during the experiment, mortality was highly species-specific and did not differ consistently between biodiversity treatments. Our results show that the effects of biodiversity on growth and mortality are uncoupled and that biodiversity affects total biomass and potentially self-thinning. The Sardinilla experiment suggests that mixed-species plantings may be a viable strategy for increasing timber yields and preserving biodiversity in tropical tree plantations.
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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 | 0.000 | 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 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".