Island Living Indirectly Affects Hair Glucocorticoid Levels in a Small Mammal
Bibliographic record
Abstract
Island vertebrates that are small on the mainland tend to be larger and exhibit tamer behavior than their mainland conspecifics—a combined set of characteristics known as “island syndrome.” Such island-specific traits are often attributed to lower predation pressure on islands than on the mainland. While the morphology and behavior of island vertebrates has received significant attention, relatively few studies have compared physiological traits between island and mainland populations. Given that hormones such as glucocorticoids are involved in responding to predation, it is reasonable to test whether island populations that have demonstrated characteristics of island syndrome also have different glucocorticoid levels than their mainland conspecifics. Here, we used a long-term museum collection of deer mice (Peromyscus maniculatus) obtained from two archipelagos and two mainland regions to test the hypothesis that island syndrome includes changes in time-averaged corticosterone levels, as measured in hair. As predicted by island syndrome, deer mice from islands were structurally larger and heavier for their given structural size than their mainland conspecifics. When we compared size-matched individuals (i.e., holding size constant), hair corticosterone levels did not differ between island and mainland mice. However, corticosterone levels scaled positively with body mass and condition across our sample population. This led to a relative increase in corticosterone levels among median-sized mice from islands relative to median-sized mice from mainland populations. We conclude that island syndrome does include effects on deer mouse stress physiology but only indirectly through the evolution of larger body size in island populations.
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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 | 0.000 |
| 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) | 0.001 | 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".