Disturbance cue communication is shaped by emitter diet and receiver background risk in Trinidadian guppies
Bibliographic record
Abstract
Abstract In animal communication systems, individuals that detect a cue (i.e., “receivers”) are often influenced by characteristics of the cue emitter. For instance, in many species, receivers avoid chemical cues that are released by emitters experiencing disturbance. These chemical “disturbance cues” appear to benefit receivers by warning them about nearby danger, such as a predator’s approach. While the active ingredients in disturbance cues have been largely unexplored, by-products of metabolized protein are thought to play a role for some species. If so, the content (quality) and volume (quantity) of the emitter’s diet should affect their disturbance cues, thus altering how receivers perceive the cues and respond. Guppies Poecilia reticulata are a species known to discriminate among disturbance cues from different types of donors, but dietary variation has yet to be explored. In this study, we found evidence that diet quality and quantity can affect disturbance cues released by guppy emitters (i.e., experimental “donors”). Receivers discriminated between donor cue treatments, responding more strongly to cues from donors fed a protein-rich bloodworm diet (Experiment 1), as well as an overall larger diet (Experiment 2). We also found that receivers exposed to higher background risk were more sensitive to disturbance cue variation, with the strongest avoidance responses displayed by high-risk receivers toward disturbance cues from donors fed the high-quality diet. Therefore, diet, and perhaps protein specifically, affects either the concentration or composition of disturbance cues released by guppies. Such variation may be important in information signaling in social species like the guppy.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".