Responses of different herbivore guilds to nutrient addition and natural enemy exclusion
Bibliographic record
Abstract
We experimentally investigated the effects of plant quality and natural enemies on the abundance of different herbivore guilds on oak trees. Two oak species (Quercus laevis and Q. geminata) and four guilds of leaf herbivores (leaf miners, gall-formers, leaf-rollers, and chewers) were studied using a factorial design that manipulated predation/parasitism pressure and plant nutritional quality. Forty plants of each species were divided into four treatments: 1) control plants (nutrients and natural enemies unaltered); 2) nutrients added, natural enemies unaltered; 3) nutrients unaltered, natural enemies removed; and 4) nutrients added and natural enemies excluded. Fertilized plants exhibited significantly higher foliar nitrogen for both oak species, and tannins tended to increase over time and decrease with fertilization, but only for Q. geminata was this trend significant. Fertilized plants supported significantly higher densities of all herbivore guilds than did unfertilized plants, but exclusion of natural enemies did not significantly affect herbivore abundance for any guild studied. Our results demonstrate that all herbivores on oaks, regardless of guild type, respond more strongly to bottom-up effects such as host-plant quality than to top-down effects caused by natural enemies.
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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 | 0.001 |
| 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".