Female assessment of male functional fertility during mate choice in a promiscuous fish
Bibliographic record
Abstract
Abstract Sexual selection should favour females that can assess the functional fertility of available sexual partners and avoid mating with recently mated, sperm‐depleted males. Our current understanding of the sensory mechanism(s) underlying female assessment of males based on their functional fertility and avoidance of sperm‐depleted males is incomplete. Female Trinidadian guppies ( Poecilia reticulata) are known to avoid mating with males that they had previously observed mating with other females. Here, we investigated experimentally the proximate sensory cues that they use to distinguish between paired size‐ and colour‐matched mated and unmated males in the absence of visual public information on their prior mating histories. When only water‐borne chemical cues from the males were available, females avoided the previously mated male and preferred the unmated one, but they chose randomly when only male visual cues (and no chemical cues) were available. They also preferred unmated over mated males when freely swimming with them in a more sensorially complex environment with multiple male cues (i.e., visual, chemical and mechanical cues) concurrently available. Females exhibited no preference for either stimulus males when both were unmated, irrespectively of the sensory environment. These novel results suggest that, in the absence of prior visual public information on the recent mating histories of males, female guppies use olfactory cues putatively emitted by mated males to avoid mating with them. The source and nature of the implicated olfactory cues and the fitness benefits gained by female guppies in sexually preferring males that have not recently mated remain unknown and warrant further research.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".