HOW WELL DO MATING FREQUENCY AND DURATION PREDICT PATERNITY SUCCESS IN THE POLYGYNANDROUS WATER STRIDER AQUARIUS REMIGIS?
Bibliographic record
Abstract
The relationship between mating success and paternity success is a key component of sexual selection but has seldom been estimated for species in which both sexes mate with many partners (polygynandry). We used a modification of Parker's sterile male technique to measure this relationship for the water strider Aquarius remigis in 47 laboratory populations simulating natural conditions of polygynandry. We also tested the hypothesis that prolonged copulation, a characteristic of this species, enhances paternity success. Mating behavior and paternity success were assayed for four days while males and females freely interacted. Paternity success was also assayed for an additional 7 days when females were isolated from males. Mating success significantly predicted paternity success and accounted for < or = 36% of the variance. Copulation duration was negatively related to both mating success and paternity success and did not explain any of the residual variance in paternity success. Thus, we found no evidence that prolonged copulation functions as a paternity assurance strategy in this species. Comparisons of sterile and fertile males suggested that paternity success is directly influenced by the quantity of sperm transferred. Our results support previous studies that have used mating success to estimate sexual selection, but also highlight the potential importance of sperm competition and other postinsemination processes.
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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 | 0.003 |
| 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".