Male-Male Competition in a Mixed-Mating Fish
Bibliographic record
Abstract
Mating systems that comprise a mixture of pure males and self-fertilising hermaphrodites remain an evolutionary enigma. In particular, our understanding of the sexual selection pressures associated with such mating systems is nascent. Males can only reproduce by fertilising hermaphrodites’ eggs, but hermaphrodites can also fertilise their own eggs and gain a genetic advantage by doing so. Consequently, there should be intense competition among males to access hermaphrodites. Here, we test the importance of male size, colour and heterozygosity in predicting the outcome of male–male competition using the mangrove rivulus, which has a male-hermaphrodite mixed-mating system. We pitted males against one another in dyadic laboratory trials to develop a dominance score for each male. We then correlated these scores with male length, several components of male colour, and heterozygosity. Male size was the only significant correlate of dominance: larger males dominated smaller males, implying selection for large male size. However, male mangrove rivulus are similar in size to hermaphrodites, indicating that directional selection for large body size in males is no greater than it is in hermaphrodites. Across all trials, colour was unrelated to dominance, but contests between similarly sized males were usually won by more colourful individuals. As mangrove rivulus are dichromatic, we suspect that male colour may prove to be more important in mate choice than we found it to be in intrasexual competition. Heterozygosity did not explain dominance directly, but correlated strongly with male size, implying an indirect role in intrasexual competition.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".