Manipulating Individual State During Migration: Carry‐Over Effects of Cumulative Stress on Survival
Bibliographic record
Abstract
ABSTRACT The stress response is a mechanism to cope with unpredictable events and minimize immediate threats to survival. However, cumulated stress due to multiple stressors can have long‐term deleterious effects on fitness by impairing reproduction and survival. This aspect of stress physiology and its consequences on demographic traits have received little attention in wild populations, and such studies are mostly observational. Here, we investigate the demographic consequences of multiple stressors (fasting and prolonged captivity) experimentally imposed during spring migration on greater snow geese ( Anser caerulescens atlantica ). In 2009, female snow geese were captured at a spring staging site and kept in captivity for up to 4 days with or without access to food. Blood samples were taken at capture, banding, and release to measure corticosterone (CORT) levels, a stress‐response hormone, during the experiment. CORT response peaked within the first hours after capture and decreased during the following days in captivity. We observed that stress‐induced CORT levels of captive individuals at release depended on their pre‐experiment body condition, but not the stress‐induced peak CORT response. We showed no link with subsequent reproductive success, but we detected a negative carry‐over effects of food deprivation on survival in the following year. Pre‐treatment spring body condition and stress‐induced CORT levels had marginal effects on survival. We showed that cumulated stressors could have carry‐over effects on survival and that the intensity of the hormonal response can ultimately affect survival.
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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".