Among‐individual behavioral responses to predation risk are invariant within two species of freshwater snails
Bibliographic record
Abstract
Abstract Prey behavioral response to predation risk drives a range of ecological and evolutionary processes. Key to these effects is the degree to which conspecifics exhibit consistent individual differences in their response to risk or instead follow a mean population‐level pattern. Here, we employed the behavioral reaction norm framework to quantify among‐individual variation in average predator avoidance behavior (i.e., behavioral types) and the behavioral response to risk (i.e., individual plasticity) in two snail species (Helisoma trivolvis and Physa acuta) that differ in their vulnerability to predators. While both snail species exhibited substantial variation in behavioral types, individual plasticity in response to risk was remarkably invariant—both snail species increased avoidance behavior with increasing risk, but all conspecific individuals followed the population‐level pattern (i.e., parallel reaction norms). Instead, individual snails differed in how they adjusted their behavior over the course of repeated behavioral assays (n = 12 per individual), with some exhibiting increased sensitization to risk cues and others habituation. We further show that among‐individual behavioral variation, both in behavioral types and in individual responses to repeated assays, was sometimes correlated with physiological traits, providing potential mechanisms for the maintenance of this variation. In total, our results indicate that behavioral types and individual plasticity vary at different hierarchical scales (individual‐ vs. population‐level, respectively) in freshwater snails, which has implications for species interactions and the evolution of predator avoidance behavior.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".