The Personality Behind Cheating: Behavioural Types and the Feeding Ecology of Cleaner Fish
Bibliographic record
Abstract
Abstract The complex mutualistic relationship between the cleaner fish ( Labroides dimidiatus ) and their ‘clients’ in many reef systems throughout the world has been the subject of debate and research interest for decades. Game‐theory models have long struggled with explaining how the mixed strategies of cheating and honesty might have evolved in such a system and while significant efforts have been made theoretically, demonstrating the nature of this relationship empirically remains an important research challenge. Using the experimental framework of behavioural syndromes, we sought to quantitatively assess the relationship between personality and the feeding ecology of cleaner fish to provide novel insights into the underlying mechanistic basis of cheating in cleaner‐client interactions. First, we observed and filmed cleaner fish interactions with heterospecifics, movement patterns and general feeding ecology in the wild. We then captured and measured all focal individuals and tested them for individual consistency in measures of activity, exploration and risk taking (boldness) in the laboratory. Our results suggest a syndrome incorporating aspects of personality and foraging effort are central components of the behavioural ecology of L. dimidiatus on the Great Barrier Reef. We found that individuals that exhibited greater feeding effort tended to cheat proportionately less and move over smaller distances relative to bolder more active, exploratory individuals. Our study demonstrates for the first time that individual differences in personality might be mechanistically involved in explaining how the mixed strategies of cheating and honesty persist in cleaner fish mutualisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".