Chronic stress and body condition of wolf-killed prey in Prince Albert National Park, Saskatchewan
Bibliographic record
Abstract
Abstract Chronic stress and poor body condition can cause adverse physiological and behavioural responses and may make animals more vulnerable to predation. We examined hair cortisol concentration (HCC) and marrow lipid content, as bioindicators of chronic stress and body condition, respectively, of bison (Bison bison bison), moose (Alces alces) and white-tailed deer (Odocoileus virginianus) killed by wolves (Canis lupus) in Prince Albert National Park (PANP), Saskatchewan, Canada. The Sturgeon River plains bison population in PANP is one of only a few wild populations of plains bison in their historical range in Canada and has experienced a decline of around 50% since 2005. We expected wolf-killed bison to have elevated HCC compared to human-harvested bison and that there would be a negative relationship between HCC and marrow lipids among wolf-killed animals. We compared HCC between different mortality sources for bison (wolf-killed n = 20 or human-harvested n = 23) and found that HCC was significantly elevated in wolf-killed bison (̄ = 7.56 ± 1.35 pg/mg). We found that HCC, species, sex and snow depth were all significant predictor variables of marrow lipid content of bison (n = 14), moose (n = 11) and deer (n = 27). Bison displayed the strongest negative correlation between HCC and marrow lipid content (r2 = 0.31). Our results suggest that chronic stress and poor body condition make prey more vulnerable to predation by wolves. HCC and marrow lipid content can provide reliable indicators of the physiological response of animals to stressors and may provide information on expected predator success that can be used to predict predator population dynamics.
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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 | 0.000 |
| 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 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".