Tree diversity enhances predation by birds but not by arthropods across climate gradients
Bibliographic record
Abstract
Tree diversity can promote both predator abundance and diversity. However, whether this translates into increased predation and top-down control of herbivores across predator taxonomic groups and contrasting environmental conditions remains unresolved. We used a global network of tree diversity experiments (TreeDivNet) spread across three continents and three biomes to test the effects of tree species richness on predation across varying climatic conditions of temperature and precipitation. We recorded bird and arthropod predation attempts on plasticine caterpillars in monocultures and tree species mixtures. Both tree species richness and temperature increased predation by birds but not by arthropods. Furthermore, the effects of tree species richness on predation were consistent across the studied climatic gradient. Our findings provide evidence that tree diversity strengthens top-down control of insect herbivores by birds, underscoring the need to implement conservation strategies that safeguard tree diversity to sustain ecosystem services provided by natural enemies in forests.
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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) | 0.001 | 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 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".