Effects of Age and Experience on Male Mate Choosiness
Bibliographic record
Abstract
Abstract Mate choosiness by males has been documented in many taxa but we still do not know how it varies with age even though such variation can be important for our understanding of sexual selection on females. Theory provides conflicting predictions: young males, who are less attractive to females than older males, may be less choosy, or older males, who face fewer expected future mating opportunities, may be less choosy. In our experiments with fruit flies ( D rosophila melanogaster ), young (1‐d‐old) males spent relatively less time courting recently mated females than did mature (4‐d‐old) males. Overall, there was a gradual decline in male mate choosiness from age 1–7 d. As male age was correlated with the duration of deprivation from females, we tested for the effect of deprivation and found that same‐age males previously exposed to females were choosier than female‐deprived males. We also assessed key male parameters that could affect choosiness and found that, compared to mature males, young males were less attractive to females, less competitive in intramale interactions and less fertile. Although the lesser attractiveness and competitiveness should select for lesser mate choosiness in young males, their limited fertility and more expected future mating opportunities seem to override the other factors and lead to high mate choosiness in young males. Overall, our data indicate that young males just after reaching sexual maturity are choosy and that subsequent exposure to females can maintain high levels of male mate choosiness with age. Hence, males can contribute much more to sexual selection than previously appreciated.
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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) | 0.000 | 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".