Understanding the mismatch between behaviour and development in a novel host-parasitoid association
Bibliographic record
Abstract
Foraging parasitoid females should preferentially oviposit on hosts most suitable for progeny development to maximize their fitness. However, the introduction of a new host species may disrupt the link between the reliability of the cues and the expected adaptive outcome of female choice, leading to an evolutionary trap. This mismatch between behavioural acceptance and lack of development exists for North American and European egg parasitoids (Scelionidae) that encounter invasive Halyomorpha halys in areas where this exotic host has recently established. To explain this mismatch, we utilized an L9 orthogonal array design to assess and rank the influence of several critical factors characterizing host resource (host species, egg age, egg status, and surface wash) on behaviour (acceptance, patch residence and patch exploitation) and development of North American native Trissolcus euschisti egg parasitoid. Our results indicate that the host egg age is most important for behaviour, but is least influential for development of the progeny. This study suggests that the maladaptive decision to oviposit in an unsuitable host is due to a mismatch between the cues that females use, and the subsequent expected outcome of this choice. Therefore, it is the relative importance of individual factors when assessed simultaneously that influences the decision-making of female parasitoids.
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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 | 0.000 |
| 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".