Life history trade-offs in glucocorticoid-mediated habitat selection
Bibliographic record
Abstract
Abstract The cort-adaptation and cort-fitness hypotheses both propose glucocorticoids produced by parents mediate trade-offs between their own survival and that of their offspring. The contribution of glucocorticoids to offspring provisioning can quantify these trade-offs because provisioning poses a risk to parents. However, attributing provisioning behaviour to glucocorticoids is difficult because glucocorticoids often drive foraging behaviours to store energy for later provisioning. We compared the effects of glucocorticoids on habitat selection before and after calving to test for the trade-offs female elk make when provisioning offspring. Despite finding that female elk with elevated glucocorticoids selected more strongly for high-risk, high-forage cropland, we found no difference in glucocorticoid production nor a significant change in the effect of glucocorticoids on cropland selection at calving time when lactating elk required the more energy. However, we found a gradual increase in the effect of glucocorticoids on cropland selection by female elk as their calves grew, suggesting the growing energy requirements of calves encouraged more risky habitat selection behaviours by their parents over time. We suggest trade-offs in investment between parents and offspring across life history stages can be tested by integrating glucocorticoids into habitat selection models. Ultimately, this integration will help elucidate the adaptive function of glucocorticoids.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".