Effects of habitat complexity, dominance and personality on habitat selection: Ideal despotic cichlids
Bibliographic record
Abstract
Abstract Habitat structure can impede visibility and movement, resulting in lower resource monopolization and aggression. Consequently, dominant individuals may prefer open habitats to maximize resource gain, or complex habitats to minimize predation risk. We explored the role of dominance on foraging, aggression and habitat choice using convict cichlids (Amatitlania nigrofasciata) in a two‐patch ideal free distribution experiment. Groups of six fish of four distinct sizes first competed for shrimp in one‐patch trials in both an open and complex habitat; half the groups experienced each habitat type first. Following these one‐patch trials, each group then chose between habitat types in a two‐patch trial while competing for food. Finally, each fish underwent an individual behavioural assessment using a battery of “personality” tests to determine if behaviour when alone accurately reflected behaviour within a social context. In the one‐patch trials, dominant fish showed similar food consumption between habitats, but chased more in the complex habitat. In the two‐patch choice trials, dominants preferred and defended the complex habitat, forming an ideal despotic distribution with more than half the fish and competitive weight in the open habitat. Within the groups, individual fish differed in foraging and chasing, with repeatabilities of 0.45 and 0.23 across all treatments. Although a higher foraging rate during the individual assessment predicted foraging rate and use of the complex habitat during the group trials, aggression and boldness tests were not reflective of group behaviour. Across groups, heavier dominants and those with higher foraging rate in the open habitat used the open habitat more, suggesting that both risk and energetic state affect habitat preference in dominant convict cichlids.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".