Strategic and tactical fighting decisions in cichlid fishes with divergent social systems
Bibliographic record
Abstract
The costs and benefits of engaging in a contest will differ depending on the social situation of the individuals involved. Therefore, understanding contest behaviour can help to elucidate the trade-offs of living in differing social systems and shed light on the evolution of social behaviour. In the current study, we compared contest behaviour in two closely related species of Lamprologine cichlid fish. Neolamprologus pulcher and Telmatochromis temporalis are both pair-breeding cichlids, but N. pulcher are highly social, group-living fish, while T. temporalis display no grouping behaviour. To examine how competition varies by species, sex and familiarity, we staged same-sex conspecific contests over a shelter, a resource that is highly valued by both species, where contestants were either familiar or unfamiliar to one another. When we examined tactical and strategic components of these contests, we found that the highly social species had shorter contests and engaged in fewer costly aggressive acts than did the non-social species. Individuals of the highly social species were also more likely to resolve conflicts through the use of submissive displays, while individuals of the non-social species were more likely to flee from conflict. Familiarity increased the use of submissive displays in the highly social species but not in the less social species. Our findings suggest that conflict resolution behaviour and dominance hierarchy formation are fundamentally linked to the evolution of complex social systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".