Degradation of chemical alarm cues and assessment of risk throughout the day
Bibliographic record
Abstract
The use of chemical information in assessment of predation risk is pervasive across animal taxa. However, by its very nature, chemical information can be temporally unreliable. Chemical cues persist for some period of time after they are released into the environment. Yet, we know surprisingly little about the rate of degradation of chemical cues under natural conditions and hence little about how they function in temporal risk assessment under natural conditions. Here, we conducted an experiment to identify a concentration of fresh alarm cues that evoke a strong antipredator response in coral reef damselfish, Pomacentrus ambonensis. We then tested the rate at which these alarm cues degraded under natural conditions in ocean water, paying attention to whether the rate of degradation varied throughout the day and whether the temporal pattern correlated with physicochemical factors that could influence the rate of degradation. Fresh alarm cues released into ocean water evoke strong avoidance responses in juvenile fish, while those aged for 30 min no longer evoke antipredator responses. Fish exposed to cues aged for 10 or 20 min show intermediate avoidance responses. We found a marked temporal pattern of response throughout the day, with much faster degradation in early to mid-afternoon, the time of day when solar radiation, temperature, dissolved oxygen, and pH are nearing their peak. Ecologists have spent considerable effort elucidating the role of chemical information in mediating predator-prey interactions, yet we know almost nothing about the temporal dynamics of risk assessment using chemical information. We are in dire need of additional comparative field experiments on the rate of breakdown of chemical cues, particularly given that global change in UV radiation, temperature, and water chemistry could be altering the rates of degradation and the potential use of this information in risk assessment.
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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 | 0.000 | 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 | 0.001 |
| 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".