Mating assortment and the strength of sexual selection in a polyandrous population of Cook Strait giant weta
Bibliographic record
Abstract
Abstract Polyandry can profoundly affect the strength of pre-copulatory sexual selection acting on males because each additional mate acquired by a female means that, all else being equal, a male’s paternity share declines. However, accruing additional mates could benefit male fitness if males with greater mating success also tend to have less promiscuous females as partners. If this is indeed the case, then males should experience strong sexual selection to acquire more mates. We tested these predictions by collecting detailed mating data on male and female Cook Strait giant weta (Deinacrida rugosa) in the wild via daily radio tracking. Our sexual network-based approach indeed revealed that the most polygynous male D. rugosa mated the least polyandrous females. This finding therefore suggests that the most successful males likely face lower intensities of sperm competition and so should be selected to accrue more mates. Further, our selection analysis revealed significant pre-copulatory sexual selection on males with those having relatively smaller body size, lighter body mass, and longer legs accruing more mates than otherwise. Thus, it appears that both pre- and post-copulatory episodes of sexual selection reinforce the same male phenotype.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".