More diverse temperate forests are more resistant against non-native insect herbivores
Bibliographic record
Abstract
Abstract In general, trees suffer less damage by insect herbivores when growing in forest mixtures than in tree monocultures. Yet, most current knowledge is based on responses of native herbivores to tree diversity. Since introduced insect herbivores differ from native ones in their biotic interactions, their sensitivity to tree diversity is uncertain. We measured the damage caused by 11 non‐native herbivorous insects in monospecific and mixed forest stands in Europe. We merged these data with the results of published studies on native insects in temperate forests and applied a meta‐analytic approach to compare the effects of tree diversity on native vs. non‐native insect herbivores. We found that the damage by non‐native pest insects was reduced in mixed forest stands, that is associational resistance. The magnitude of this resistance was comparable to that measured for native herbivores. Associational resistance increased with increasing proportion of non‐host trees in the mixed forest. These results suggest that promoting mixed forests could be an effective strategy to attenuate the impact of invasion by non‐native forest pests.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".