Predation risk and mountain goat reproduction: Evidence for stress‐induced breeding suppression in a wild ungulate
Bibliographic record
Abstract
Abstract Non‐consumptive effects of predation can strongly impact reproduction and demography of prey species. Still, the underlying mechanisms that drive non‐consumptive effects are not fully understood, and the circumstances under which chronic physiological stress may mediate these effects remain unclear. Benefiting from over 23 years of environmental, physiological and demographic data, we tested the hypothesis that predation risk may impair reproduction of mountain goats through chronic elevation of physiological stress. We conducted path analyses to assess the relationships between predation risk, faecal glucocorticoid metabolites and hair cortisol concentration, and reproduction, while taking into account the potential effects of age class, sex, body mass, season and within individual variation in glucocorticoid concentration. Predation risk had a direct positive effect on the average annual faecal glucocorticoid concentration in the population, which, in turn, negatively affected the proportion of reproductive females. The same pattern was observed with hair cortisol concentration, but these results were inconclusive potentially due to methodological challenges in estimating annual average of hair cortisol at the population level. Our study presents one of the first robust evidence that stress‐mediated breeding suppression can occur in a wild ungulate following increased predation risk, thereby providing a major insight on the mechanisms underlying non‐consumptive effects of predation in wild mammals. A free Plain Language Summary can be found within the Supporting Information of this article.
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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 | 0.001 |
| 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) | 0.002 | 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".