Geographic variation in sperm traits reflects predation risk and natural rates of multiple paternity in the guppy
Bibliographic record
Abstract
Guppies (Poecilia reticulata) are models for understanding the interplay between natural and sexual selection. In particular, predation has been implicated as a major force affecting female sexual preferences, male mating tactics and the level of sperm competition. When predation is high, females typically reduce their preferences for showy males and engage more in antipredator behaviours, whereas males exploit these changes by switching from sexual displays to forced matings. These patterns are thought to account for the relatively high levels of multiple paternity in high-predation populations compared to low-predation populations. Here, we assess the possible evolutionary consequences of these patterns by asking whether variation in sperm traits reflect differences in predation intensity among four pairs of Trinidadian populations: four that experience relatively low levels of predation from a gape-limited predator and four that experience relatively high levels of predation from a variety of piscivores. We found that males in high-predation populations had faster swimming sperm with longer midpieces compared to males in low-predation populations. However, we found no differences among males in high- and low-predation populations with respect to sperm number, sperm head length, flagellum length and total sperm length.
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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 | 0.001 | 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".