Audience Effect Alters Male Mating Preferences in Zebra Finches (Taeniopygia guttata)
Bibliographic record
Abstract
The social environment of animals strongly influences the mating preferences of both the choosing and the observing individuals. Notably, there is recent evidence that polygamous males decrease their selectivity when being observed by competitors in order to direct their rivals' attention away from their true interest and, consequently, reduce sperm competition risk. Yet, other mechanisms, whose importance remains unexplored, could induce similar effects. In monogamous species with mutual choice, particularly, if males adjust their selectivity according to the risk of being rejected by their preferred mate, they should as well become less selective when potential rivals are present. Here, we investigated whether the presence of bystanders modifies male mating preferences when the risk of sperm competition is low, by carrying out mate-choice experiments with male zebra finches (Taeniopygia guttata) whose preferences for two females were measured twice: with and without an audience. We found that the presence of potential rivals had no effect on the males' choosiness. However, with an audience, they spent more time with the female that was considered as the less attractive one in the control condition. These findings support the hypothesis that monogamous males alter their mate choice decisions in the presence of a male audience to reduce the risk of remaining unpaired. Thus, our results indicate that several explanations can account for the changes in male preferences due to the presence of competitors and highlight the importance of assessing the relative role of each mechanism potentially involved, to be able to make conclusions about the effect of an audience on signal evolution.
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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) | 0.002 | 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".