A molecular diagnostic tool for the preliminary assessment of host–parasitoid associations in biological control programmes for a new invasive pest
Bibliographic record
Abstract
Evaluation of host-parasitoid associations can be tenuous using conventional methods. Molecular techniques are well placed to identify trophic links and resolve host-parasitoid associations. Establishment of the highly invasive brown marmorated stink bug, Halyomorpha halys (Hemiptera: Pentatomidae), outside Asia has prompted interest in the use of egg parasitoids (Hymenoptera: Scelionidae) as biological control agents. However, little is known regarding their host ranges. To address this, a DNA barcoding approach was taken wherein general PCR primers for Scelionidae and Pentatomidae were developed to amplify and sequence >500-bp products within the DNA barcoding region of the cytochrome oxidase I (COI) gene that would permit the identification of key players in this association. Amplification of DNA from Pentatomidae and Scelionidae was consistent across a broad range of taxa within these families, and permitted the detection of Scelionidae eggs within H. halys 1 h following oviposition. In laboratory assays, amplification and sequencing of DNA from empty, parasitized eggs was successful for both host (100% success) and parasitoid (50% success). When applied to field-collected, empty egg masses, the primers permitted host identification in 50-100% of the eggs analysed, and yielded species-level identifications. Parasitoid identification success ranged from 33 to 67% among field-collected eggs, with genus-level identification for most specimens. The inability to obtain species-level identities for these individuals is due to the lack of coverage of this taxonomic group in public DNA sequence databases; this situation is likely to improve as more species are sequenced and recorded in these databases. These primers were able to detect and identify both pentatomid host and scelionid parasitoid in a hyperparasitized egg mass, thereby clarifying trophic links otherwise unresolved by conventional methodology.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".