Evaluation of hair cortisol concentration as a biomarker of long‐term stress in free‐ranging polar bears
Bibliographic record
Abstract
Abstract Long‐term physiological stress in individual animals may be an important mechanism linking ecological change with impaired wildlife population health. In the Southern Hudson Bay (SH) subpopulation of polar bears ( Ursus maritimus ), increasing stress associated with climate warming may be related to declining body condition. Accordingly, the development of tools to assess long‐term stress in this species may prove invaluable for conservation efforts in this threatened population. The measurement of hair cortisol concentration (HCC) has shown promise as a potential biomarker of long‐term stress in free‐ranging bears. However, to serve as a useful management tool, factors influencing HCC in polar bears must be identified and then revealed to establish linkages between environmental conditions and the fitness of individual animals. We determined HCC (median = 0.48 pg/mg [range = 0.16–2.26 pg/mg]) in 185 polar bears captured in southern Hudson Bay from 2007 to 2009. HCC was influenced by sex, family group status, and capture period but not by body region or hair type. Using models developed through a combination of hypothesis testing and information theory, we also determined that HCC was negatively associated with growth indices (length, mass, and body condition index) linked to fitness in polar bears. Additional research will be required across several polar bear populations to establish the utility of HCC as a tool for polar bear conservation. © 2012 The Wildlife Society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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) | 0.005 | 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".