Data and R codes from: Effects of human disturbance on risk-taking behavior in painted turtles
Bibliographic record
Abstract
Animals are exposed to high levels of anthropogenic disturbance, which has profound consequences for population persistence. Individuals can adjust their behavior plastically when faced with perturbations in their environment and may show consistent differences in the way they perceive and respond to risky situations. Over time, this variability among individuals in response to risk can affect the dynamics of populations exposed to human disturbance. Thus, understanding how animals cope behaviorally with human disturbance is important, especially for species vulnerable to human perturbations, such as turtles. In this context, we evaluated whether risk-taking behaviors are consistent within individual painted turtles (<em>Chrysemys picta</em>) and assessed how these behaviors are related to the extent of human disturbance along the Rideau Canal, Ontario, Canada. Specifically, we conducted repeated measurements of the number of active defensive behaviors used during handling and the time taken to escape a floating platform for a total of 730 painted turtles (1117 observations) from 22 sites varying in human disturbance along the canal. We also quantified the emergence of the turtles from the water after escaping the platform. First, individual painted turtles showed consistent differences in all risk-taking behaviors. Second, painted turtles in areas with high boat activity displayed more active defensive behaviors, while turtles from sites in proximity to more houses with access to the canal used fewer. Our study highlights the importance of studying animal behavior to better understand the impact of human activities on animal populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".