Male Mating History Influences Female Mate Choice in the Trinidadian Guppy (<i>Poecilia reticulata</i>)
Bibliographic record
Abstract
Abstract Based on the phenotype‐linked fertility hypothesis, sexual selection should favour females that can accurately assess the recent mating history of available sexual partners and preferentially avoid mating with recently‐mated males [who may be sperm depleted (SD)] so as to minimize the risk of their eggs not being fertilized. This hypothesis has received to date only limited attention and empirical support. Therefore, in the current study, we investigated experimentally whether females of a vertebrate species, the Trinidadian guppy (Poecilia reticulata), are able to assess the recent mating history of males, and thus potentially their functional fertility, and choose to avoid mating with males that appear to have recently mated and who may be sperm limited. Individual virgin females were first given a dichotomous choice between a male that had not been recently observed to interact sexually with another female (i.e. not sperm‐depleted) and another male that had been observed to interact sexually with a female (i.e. potentially sperm‐depleted) as sexual partners. Paired males were matched for body length and coloration. Immediately following this test, the focal females were subjected to a free‐swimming mate‐choice test using the same paired stimulus males. As predicted, on average, female guppies avoided the apparently recently‐mated (and potentially sperm‐depleted) male and exhibited a significant preference for the other male not recently observed mating (and thus not likely sperm limited) during both tests. We do not yet fully understand the underlying mechanisms of this preference. Therefore, further research on the particular cues that females use to assess the recent mating history and fertility status of males is required.
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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) | 0.003 | 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".