Meta-analysis reveals between-population differences affect the link between glucocorticoids and population health
Bibliographic record
Abstract
Glucocorticoids are a popular tool for monitoring health of animal populations because they can increase with environmental stressors and can indicate chronic stress. However, individual responses to stressors create variation in the glucocorticoid-fitness relationship within populations. The inconsistency in this relationship calls into question the widespread use of glucocorticoids in conservation. We investigated the sources of variation in the glucocorticoid-fitness relationship by conducting a meta-analysis across a diverse set of species exposed to conservation-relevant stressors. We first quantified the extent to which studies inferred population health from glucocorticoids without first validating the glucocorticoid-fitness relationship in their own populations. We also tested whether population-level information like life history stage, sex and species longevity influenced the relationship between glucocorticoids and fitness. Finally, we tested for a universally consistent relationship between glucocorticoids and fitness across studies. We found more than half of peer-reviewed studies published between 2008 and 2022 inferred population health solely based on glucocorticoid levels. While life history stage explained some variation in the relationship between glucocorticoids and fitness, we found no consistent relationship between them. Much of the variation in the relationship could be the result of idiosyncratic characteristics of declining populations, such as unstable demographic structure, that coincided with large amounts of variation in glucocorticoid production. We suggest that conservation biologists capitalize on this variation in glucocorticoid production by declining populations by using the variance in glucocorticoid production as an early warning for declines in population health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".