Assessing Stress in Arctic Lemmings: Fecal Metabolite Levels Reflect Plasma Free Corticosterone Levels
Bibliographic record
Abstract
Interest in the ecology of stress in wild populations has triggered the development of noninvasive methods for quantifying stress hormones. Measurement of fecal corticosteroid metabolites (FCMs) is one such method, but it is still unclear whether FCMs can be a reliable proxy of free plasma glucocorticoids. To assess the validity of this assumption, we carried out a robust assessment on brown lemmings (Lemmus trimucronatus) from Bylot Island, Nunavut, Canada, that were hand captured and anesthetized and related plasma glucocorticoid levels to fecal metabolite glucocorticoid levels. We examined endogenous factors that could explain interindividual variability. Blood corticosterone was measured from samples obtained on capture and 30 min later, and FCM levels were measured from animals kept in captivity for 72 h. Plasma free corticosterone increased 135-fold over baseline values 30 min after capture, which confirmed that initial handling was perceived as a stressor. We found that FCM levels were highly related with free (marginal [Formula: see text] = 0.53) but not with total ([Formula: see text] = 0.02) corticosterone levels, regardless of age, sex, and reproductive condition. FCM levels started increasing 2 h after capture and reached maximum levels 4 h after capture. No circadian rhythm in FCMs was found. Plasma total corticosterone levels were much higher in adult females compared with adult males, but this difference was much smaller when measuring free corticosterone levels and FCM levels. Our results suggest that FCM levels are good measures of stress by being closely related to plasma free corticosterone levels in brown lemmings.
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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".