Maternal Gestational Cortisol and Testosterone Are Associated with Trade-Offs in Offspring Sex and Number in a Free-Living Rodent (Urocitellus richardsonii)
Bibliographic record
Abstract
The adaptive manipulation of offspring sex and number has been of considerable interest to ecologists and evolutionary biologists. The physiological mechanisms that translate maternal condition and environmental cues into adaptive responses in offspring sex and number, however, remain obscure. In mammals, research into the mechanisms responsible for adaptive sex allocation has focused on two major endocrine axes: the hypothalamic pituitary adrenal (HPA) axis and glucocorticoids, and the hypothalamic pituitary gonadal (HPG) axis and sex steroids, particularly testosterone. While stress-induced activation of the HPA axis provides an intuitive model for sex ratio and litter size adjustment, plasma glucocorticoids exist in both bound and free fractions, and may be acting indirectly, for example by affecting plasma glucose levels. Furthermore, in female mammals, activation of the HPA axis stimulates the secretion of adrenal testosterone in addition to glucocorticoids (GCs). To begin to untangle these physiological mechanisms influencing offspring sex and number, we simultaneously examined fecal glucocorticoid metabolites, free and bound plasma cortisol, free testosterone, and plasma glucose concentration during both gestation and lactation in a free-living rodent (Urocitellus richardsonii). We also collected data on offspring sex and litter size from focal females and from a larger study population. Consistent with previous work in this population, we found evidence for a trade-off between offspring sex and number, as well as positive and negative correlations between glucocorticoids and sex ratio and litter size, respectively, during gestation (but not lactation). We also observed a negative relationship between testosterone and litter size during gestation (but not lactation), but no effect of glucose on either sex ratio or litter size. Our findings highlight the importance of binding proteins, cross-talk between endocrine systems, and temporal windows in the regulation of trade-offs in offspring sex and number.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".