Experience with mating receptivity cues affects sexual behaviour of male guppies, but not their strength of preference towards receptive females
Bibliographic record
Abstract
Abstract Females are traditionally presented as the choosier sex, selecting males based on the quality of their traits. Yet, there is increasing evidence that male mate choice is also important, even in species without male parental care. Social environment and learning are key factors in determining mate preference, and animals are able to use the information they gather from previous experience to potentially increase their odds of obtaining a high-quality mate. We examined how the social environment affects male mate choice in the guppy ( Poecilia reticulata ). We evaluated whether male guppies with previous social experience of female receptivity cues learn to prefer and adapt their behavioural repertoire towards females with higher receptiveness levels, as this represents an optimal use of time and energy and is more likely to result in insemination. For this, we measured sexual preference and behaviour for receptive females in no-choice and dichotomous choice tests using guppy males experienced or naïve to female receptivity cues. Experience with receptivity cues did not change the strength of preference towards receptive females. However, male guppies that had previous experience with female receptivity cues adapted their mating tactic compared to naïve males. The change in mating tactics but lack of preference towards receptive females shows that the influence of social learning is present but might be weaker than predicted in this species. Furthermore, these results provide further support to studies of female mate choice suggesting mating status is not a key factor driving the strength of sexual preferences in natural populations.
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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".