Animal behaviour and algal camouflage jointly structure predation and selection
Bibliographic record
Abstract
Trait variation can structure interactions between individuals, thus shaping selection. Although antipredator strategies are an important component of many aquatic systems, how multiple antipredator traits interact to influence consumption and selection remains contentious. Here, I use a common larval dragonfly (Epitheca canis) and its predator (Anax junius) to test for the joint effects of activity rate and algal camouflage on predation and survival selection. I found that active and poorly camouflaged Epitheca were more likely to be consumed, and thus, survival selection favoured inactive and well-camouflaged individuals. Notably, camouflage dampened selection on activity rate, likely by reducing attack rates when Epitheca encountered a predator. Correlational selection is therefore conferred by the ecological interaction of traits, rather than by opposing selection acting on linked traits. I suggest that antipredator traits with different adaptive functions can jointly structure patterns of consumption and selection.
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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".