A comparison of molecular screening <i>versus</i> dissection and rearing methods to estimate parasitism of <i>Lygus</i> nymphs by <i>Peristenus</i> wasps: size matters
Bibliographic record
Abstract
Abstract Several broadleaf crops on the Canadian prairies suffer economic damage by Lygus bugs (Hemiptera: Miridae), populations of which are suppressed by parasitoids in the genus Peristenus (Hymenoptera: Braconidae). We used three different methods to assess levels of this parasitism for different instars of Lygus collected in southern Alberta, Canada. Screening Lygus for Peristenus DNA using a molecular polymerase chain reaction (PCR) method identified levels of parasitism ranging from 35 (second and third instars) to 47 (fifth instars) per cent. With dissection, parasitoids were recovered from 13 (second instars) to 44 (fifth instars) per cent of Lygus. For Lygus collected in the field and reared in the lab, Peristenus emerged from about 22 per cent of individuals. Our results show that use of PCR or dissection for fifth-instar larvae provides comparable estimates of parasitism. For earlier instars, PCR identifies levels of parasitism undetected using dissection – that is, 2.7-fold more for second instars in the present study. For the purposes of pest management and conservation biological control, dissection can provide adequate estimates of parasitism to inform a decision to reduce insecticides to protect Peristenus 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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".