Conditional syndromes: Effect of human disturbance and age on the correlation between flight initiation distance and vigilance in marmots
Bibliographic record
Abstract
Abstract Behavioral syndromes—suites of correlated behaviors across different situations and contexts—are widespread and can have important ecological consequences because correlations between distinct behaviors shape how animals respond to changing environmental conditions and can limit behavioral plasticity. Behaviors such as vigilance, foraging, and exploration are correlated in many species and thus constitute a syndrome. Studying the structure of such syndromes is important to understand potential constraints on an animal’s behavioral response to the environment. Importantly, we know relatively little about antipredator behavioral syndromes and how their structure is associated with environmental conditions. Here, we estimated the correlation between two antipredator behaviors in yellow-bellied marmots ( Marmota flaviventer ): flight initiation distance (FID), which quantifies the flightiness of an animal in response to a potential predator and time allocation to vigilance while foraging, which represents an individual’s baseline level of wariness. We also examined the correlation between these traits under two different human disturbance levels by fitting a bivariate model on data collected over 18 years from 739 individuals. We found a modest positive among-individual correlation between FID and vigilance in adults, but no correlation between those variables in the much larger yearling cohort, nor when datasets for yearlings and adults were combined. We found no support for the hypothesis that human disturbance changed the structure of the syndrome (when present). Our study suggests that antipredator syndromes may be age-specific, and thus constraints on the independent expression of the behaviors underlying those are age-specific as well.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".