Differential prey utilization by the generalist predator <i>Coleomegilla maculata lengi</i> according to prey size and species
Bibliographic record
Abstract
Abstract Prey utilization by the generalist predator Coleomegilla maculata lengi Timb. (Coleoptera: Coccinellidae) of three sympatric lepidopterous species was quantified in relation with prey size (age) and prey species. Based on optimal foraging theory, we argued that costs associated with the utilization of small and large prey are higher than those of intermediate prey size. As a result, we expected a higher prey consumption rate on intermediate prey size leading to a convex prey consumption curve. Laboratory experiments showed that, within a given prey instar, Coleomegilla maculata lengi preyed more on Plutella xylostella (L.) compared to Artogeia rapae (L.) and Trichoplusia ni (Hübner). Generally, prey consumption rate by Coleomegilla maculata lengi on the three prey species decreased with increasing immature prey size (age). The predation efficacy of Coleomegilla maculata lengi adults and fourth instar larvae was higher compared to younger coccinellids (L2). Although, Coleomegilla maculata lengi showed a higher level of predation on smaller immature prey, we demonstrated that it is not the optimal size range for this predator. As predicted, prey weight consumption rate by Coleomegilla maculata lengi was higher at intermediate prey size leading to a convex prey utilization curve. The beneficial impact of Coleomegilla maculata lengi predation on the host plant was also estimated by using a Protection Index that considers the differential predation caused by the coccinellids and the relative importance of each pest species in terms of plant injury. Coleomegilla maculata lengi has a more significant beneficial impact when it preys on T. ni immatures.
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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 | 0.000 | 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".