Seasonal plasticity in neuroendocrine mechanisms relevant to year-round territorial aggression in a wild teleost fish
Bibliographic record
Abstract
ABSTRACT Animals experience cyclical environmental changes, such as seasons, that require physiological adjustments to support different behaviors. Although many behaviors occur only during specific periods, some species, like Gymnotus omarorum , display territorial aggression year-round, making them valuable models to study seasonal plasticity in the mechanisms maintaining stable behavioral outputs. G. omarorum is a teleost fish in which neuroestrogens have been shown to play a key role in non-breeding aggression. Here, we quantified circulating hormone levels and gene expression in the social behavior network of wild breeding and non-breeding individuals. During the non-breeding season, both sexes exhibited elevated circulating androgen levels, providing potential substrates for local estrogen synthesis. Consistently, brain aromatase and estrogen receptor expression were also upregulated, suggesting an increased capacity for local estrogen synthesis and signaling. Our findings provide the first evidence in a teleost of seasonal plasticity in the mechanisms underlying territorial aggression. Comparisons with birds and mammals reveal both shared and lineage-specific strategies, highlighting common endocrine principles while revealing the evolutionary diversity of solutions to maintain a stable behavioral phenotype across changing seasonal contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".