Paternal Genetic Effects on Foraging Decision‐Making Under the Risk of Predation
Bibliographic record
Abstract
Abstract Foraging behavior under the risk of predation has interested biologists for decades. Here, we examine paternal genetic effects on foraging decisions of bluegill ( Lepomis macrochirus ) larvae sired by males adopting alternative life histories. We use split in vitro fertilization to generate maternal half‐siblings sired by either a ‘parental’ male or a ‘cuckolder’ male. Immediately, upon the switch to exogenous feeding, we fed the larvae ad libitum for 2 d. We then starved the larvae for between 12 and 17 h, following which we subjected them to a dichotomous choice foraging trial, where one side of a test tank posed a risky foraging habitat and the other posed a safe foraging habitat. Equal amounts of food were simultaneously introduced to both sides of the tank and the proportion of individuals on either side was recorded. There were significantly fewer cuckolder offspring foraging on the risky side of the tank when compared with their parental half‐siblings indicating that cuckolder offspring took fewer risks than parental offspring. These results demonstrate a paternal genetic effect (sire life history) on foraging behavior. We ruled out energetic state as a possible explanation for this difference because the half‐siblings did not differ in body length or mass. Instead, previous research suggests that cuckolder offspring have higher conversion efficiency (efficiency of converting food into soma) than parental offspring and therefore the differences in foraging behavior observed here may, in part, be attributed to genetic differences in conversion efficiency.
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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".