Effects of the vertical distribution of a root-feeding insect (<i>Anomala cuprea</i>) on the yield, mortality, and size structure of <i>Lolium perenne</i> populations at different plant densities
Bibliographic record
Abstract
The vertical distribution of belowground herbivores plays an important role in determining the performance of an individual plant, but we still do not know the effects of this distribution on plant populations. A grass (Lolium perenne L.) was, therefore, grown at two densities with three vertical distributions of the belowground herbivore Anomala cuprea Hope (Coleoptera: Scarabaeidae). The population yield decreased significantly in the treatments with a herbivore, and decreased most when the herbivore was in the top feeding zone (i.e., the shallowest soil). Plants only died when the herbivore was in the top zone or was free to move within the pot. At low plant density, the biomass of the three largest shoots decreased significantly in the presence of a herbivore, but that of shoots in the fourth and smaller ranks did not. At high plant density, shoot biomass was not significantly affected by herbivory, irrespective of plant size. The standard deviation of shoot size was larger at low densities than at high densities. At low, but not high plant densities, the standard deviation decreased when herbivory occurred in the shallowest soil layer. To our knowledge, this study is the first to demonstrate that the vertical distribution of a belowground herbivore can markedly affect the size dynamics of a plant population.
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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 | 0.000 | 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".