Transgenerational plasticity of exploratory behavior and a hidden cost of mismatched risk environments between parental sexes
Bibliographic record
Abstract
We require a better understanding of the relative contribution of different modes of non-genetic inheritance in behavioral trait development. Thus, we investigate variation in exploratory behavior, which is ecologically relevant and a target of selection. The metabolic hypothesis predicts exploratory behavior to be size-dependent across taxa. This size-dependency is cancelled out under high perceived risk, allowing us to determine the transgenerationally integrated estimated level of risk. Using fathead minnows Pimephales promelas, we manipulated perceived risk in mothers, fathers, caring males and offspring through continuous exposure to either conspecific alarm cues or to a control water treatment. In 1000 four-month old offspring, we determined body sizes and exploratory behavior. Perceived high risk in mothers, followed by personal risk, was most effective in eliminating size-dependent behavior whereas effects of paternal risk on offspring behavioral development were substantially weaker. When maternal risk is high, environmental mismatches between parents prevented offspring from responding appropriately to personal high risk. The environment of the caring male also impacted offspring behavior to a greater extent than that of its genetic parents. Our study highlights the high relative importance of maternal, personal and caring male risk environments and showcases potential costs of an environmental mismatch between parental sexes.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".