Colorful facial markings are associated with foraging rates and affiliative relationships in a wild group-living cichlid fish
Bibliographic record
Abstract
Abstract Many animals use color to signal their quality and/or behavioral motivations. Colorful signals have been well studied in the contexts of competition and mate choice; however, the role of these signals in nonsexual, affiliative relationships is not as well understood. Here, we used wild social groups of the cichlid fish Neolamprologus pulcher to investigate whether the size of a brightly colored facial patch was related to 1) individual quality, 2) social dominance, and/or 3) affiliative relationships. Individuals with larger patches spent more time foraging and tended to perform more aggressive acts against conspecific territory intruders. We did not find any evidence that the size of these yellow patches was related to social rank or body size, but dominant males tended to have larger patches than dominant females. Additionally, patch size had a rank-specific relationship with the number of affiliative interactions that individuals engaged in. Dominant males with large patches received fewer affiliative acts from their groupmates compared to dominant males with small patches. However, subordinates with large patches tended to receive more affiliative acts from their groupmates while performing fewer affiliative acts themselves. Taken together, our results suggest that patch size reflects interindividual variation in foraging effort in this cichlid fish and offer some of the first evidence that colorful signals may shape affiliative relationships within wild social groups.
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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 | 0.000 | 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) | 0.001 | 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".