Hidden Host Mortality from an Introduced Parasitoid: Conventional and Molecular Evaluation of Non-Target Risk
Bibliographic record
Abstract
Hidden trophic interactions are important in understanding food web ecology and evaluating the ecological risks and benefits associated with the introduction of exotic natural enemies in classical biological control programs. Although non-target risk is typically evaluated based on evidence of successful parasitism, parasitoid-induced host mortality not resulting in visible evidence of parasitism (i.e., nonreproductive effects) is often overlooked. The adventive establishment of Trissolcus japonicus, an exotic parasitoid of the introduced stink bug Halyomorpha halys, provides an opportunity to investigate the total impact of this parasitoid on target and non-target hosts in the field. We developed a new methodology to measure nonreproductive effects in this system, involving a species-specific diagnostic PCR assay for T. japonicus. We applied this methodology to field-deployed eggs of four pentatomid species, coupled with traditional rearing techniques. Nonreproductive effects were responsible for the mortality of an additional 5.6% of H. halys eggs due to T. japonicus, and were even more substantial in some of the non-target species (5.4–43.2%). The observed hidden mortality of native non-target species from an introduced parasitoid could change predictions about direct and indirect ecological interactions and the efficacy of biological control of the target pest.
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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 | 0.001 | 0.001 |
| 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".