Social status modulates the behavioral and physiological consequences of a chemical pollutant in animal groups
Bibliographic record
Abstract
The social environment (i.e., the suite of social interactions that occur among individuals that can result in variation in social ranks) is a commonly overlooked aspect of biology when scientists evaluate the effects of chemical contaminants. The social environment, however, represents the arena in which individual-level performance shapes group- or population-level outcomes and may therefore mediate many of the ultimate consequences of chemicals for wildlife. Here, we evaluated the role that the social environment plays in determining the consequences of pollutant exposure. We exposed groups of juvenile brown trout (Salmo trutta) to an emerging pharmaceutical pollutant that is commonly detected in freshwaters (the benzodiazepine, oxazepam) and allowed them to form dominance hierarchies. Exposure affected dominant and subordinate fish differently, causing fish to become less aggressive at high doses and subordinate fish to become more competitively successful at low doses. These perturbations had further consequences for growth, fin damage, and survival. Exposure also modulated physiological stress in the hierarchy, and social status itself affected how much oxazepam was absorbed in tissues, potentially creating a dynamic feedback loop that further influences the asymmetric effects of exposure on differing social statuses. Many effects followed a "U-shaped" dose-response curve, highlighting the importance of nonlinear, low-dose effects. Altogether, we show that social structure in animal groups can interact with and modulate the effects of an environmental contaminant. We underscore the need to account for an organism's natural ecological context, including their social environment, in future experiments and environmental risk assessments to predict the effects of chemical contaminants on wildlife.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".