Intraguild Interactions between Egg Parasitoids: Window of Opportunity and Fitness Costs for a Facultative Hyperparasitoid
Bibliographic record
Abstract
We investigated intraguild interactions between two egg parasitoids of Nezara viridula (L.) (Heteroptera: Pentatomidae), Ooencyrtus telenomicida (Vassiliev) (Hymenoptera: Encyrtidae) and Trissolcus basalis (Wollaston) (Hymenoptera: Platygastridae), as the former has the potential to be a facultative hyperparasitoid of the latter. We assessed the suitability of N. viridula eggs for the development of O. telenomicida as a function of egg age when they were unparasitized, or had been attacked by T. basalis at different times prior to exposure to O. telenomicida females. Ooencyrtus telenomicida can exploit healthy N. viridula host eggs up to 5 days of age, just prior to the emergence of N. viridula. This window of opportunity can be extended for an additional 6-7 days through interspecific competition or facultative hyperparasitism. While there are minor fitness costs for O. telenomicida as the result of interspecific larval competition, those costs are greater with facultative hyperparasitism. In choice assays O. telenomicida females discriminated between different quality N. viridula eggs, avoiding those where their progeny would have to develop as facultative hyperparasitoids of T. basalis. Results are discussed with respect to the possible effects that the costs of intraguild parasitism might have on biological control programmes.
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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 | 0.001 |
| 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".