Mechanism of mate detection in parasitoid wasps: sound and vibratory cues change with the developmental progress of future mates inside host pupal cases
Bibliographic record
Abstract
Abstract Insects including parasitoid wasps use acoustic and vibratory signals in the context of sexual communication, mate recognition, courtship and mating. Males of the parasitoid wasp Pimpla disparis V iereck ( H ymenoptera: I chneumonidae) detect insect host pupae parasitized by a conspecific female, learn their location, visit them repeatedly and remain on or near them when the prospective mate nears emergence. In the present study, the acoustic and vibratory cues that males exploit to detect the presence and track the developmental progress of a future mate inside a host pupal case are investigated. Responses are acquired from developing parasitoids ( DePa ) by airborne sound and laser D oppler vibrometer recordings, after gently stimulating each of 20 wax moth host pupae with a paintbrush on days 1–23 post parasitism. Sound and vibratory cues produced by DePa are detectable from day 7 onward and relate mostly to spinning movements. Parameters of sound and vibratory cues (amplitude, dominant frequency, upper limit of frequency band) change significantly over time and thus could ‘inform’ a visiting adult male about the stage of development of DePa . Adult males antennating a parasitized pupa and flying around it also induce vibrations, which in turn may inform DePa about the presence of a male. There is no experimental evidence for true signalling and rapid information exchange between DePa and adult males. Delaying reply signals may help DePa avoid attacks by illicit receivers of such signals, including female (hyper)parasitoids and invertebrate predators.
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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 | 0.000 |
| 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".