Species-Specific Means and Within-Species Variance in Glucocorticoid Hormones and Speciation Rates in Birds
Bibliographic record
Abstract
At macroevolutionary scales, stress physiology may have consequences for species diversification and subspecies richness. Populations that exploit new resources or undergo range expansion should cope with new environmental challenges, which could favor higher mean stress responses. Within-species variation in the stress response may also play a role in mediating the speciation process: in species with broad variation, there will always be some individuals that can tolerate an unpredictable environment, whereas in species with narrow variation there will be fewer individuals that are able to thrive in a new ecological niche. We tested for the evolutionary relationship between stress response, speciation rate, and subspecies richness in birds by relying on the HormoneBase repository, from which we calculated within- and among-species variation in baseline (BL) and stress-induced (SI) corticosterone levels. To estimate speciation rates, we applied Bayesian analysis of macroevolutionary mixtures that can account for variation in diversification rate among clades and through time. Contrary to our predictions, lineages with higher diversification rates were not characterized by higher BL or SI levels of corticosterone either at the tips or at the deeper nodes of the phylogeny. We also found no association between mean hormone levels and subspecies richness. Within-species variance in corticosterone levels showed close to zero repeatability, thus it is highly unlikely that this is a species-specific trait that influences diversification rates. These results imply that stress physiology may play a minor, if any, role in determining speciation rates in birds.
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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 | 0.000 | 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 | 0.000 |
| 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".