Behavioural reactions of three-spined sticklebacks to simulated risk of predation—Effects of predator distance and movement
Bibliographic record
Abstract
The behavioural response of animals to predation risk commonly depends on the behaviour of potential predators. Here, we report an experiment investigating effects of predator model (a life-like wooden trout model) distance and movement on the behaviour of three-spined sticklebacks Gasterosteus aculeatus L. in a standardized experimental setting. When the predator model was immobile, the behaviour of the sticklebacks could, in general, not be clearly distinguished from a no-predator control treatment. When moving the predator 41 cm towards the stickleback, clear anti-predator behaviours were observed. However, behavioural expression depended on the distance to the predator. At the two farthest distances (approaching from 129 to 88 cm and from 170 to 129 cm), the sticklebacks approached the predator and spent little time freezing. At the two closest distances (approaching from 88 to 47 cm and from 47 to 6 cm), the sticklebacks increased the distance to the predator model and froze their movements. These results suggest that the closest-distance groups showed avoidance behaviour, whereas the farthest-distance groups instead appeared to start inspecting the potential predator. This provides evidence for conditional anti-predator behaviour and highlights the importance of considering distance to, and movement of predator models when interpreting data from standardized behavioural trials.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".