Chemical Predator Inspection in a Characin Fish (<i>Hemigrammus erythrozonus,</i>Characidae, Ostariophysi): The Effects of Mixed Predator Diets
Bibliographic record
Abstract
Many prey organisms will approach (inspect) potential predators, primarily to assess local risk of predation. It has been demonstrated that Ostariphysan prey fishes can detect conspecific alarm pheromones in the diet of potential predators and use this chemical information to reduce their risk of predation while still gaining significant benefits associated with predator inspection. We conducted the current study to examine the possible effects of mixed diets on the use of these chemical predator diet cues during inspection visits. Shoals of four glowlight tetras ( Hemigrammus erythrozonus ) were exposed to Jack Dempsey cichlids ( Cichlasoma octofaciatum ) which had been fed diets consisting of: 100% tetras (with alarm pheromone); 75% tetra, 25% swordtail ( Xiphophorus helleri , which lack a recognizable alarm pheromone); 25% tetra, 75% swordtail; or 100% swordtails. Tetras significantly increased their anti‐predator behaviour in response to predators fed 100% tetra or the two mixed predator diets, but not when exposed to predators fed a 100% swordtail diet. Likewise, we observed significant differences in inspection behaviour. Tetras took longer to initiate an inspection, inspected in smaller groups and directed a greater proportion of inspection visits towards the tail region of the predator when it had been fed 100% tetra or either of the two mixed prey diets. We found no significant differences in either anti‐predator or inspection behaviour among the three diet treatments containing tetras. These data strongly suggest that glowlight tetras are capable of detecting relatively small amounts of conspecific alarm pheromone in the diet of potential predators and that they modify their behaviour based on the presence or absence of these cues.
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 | 0.000 | 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".