Personality influences wildlife responses to aversive conditioning
Bibliographic record
Abstract
ABSTRACT Ungulate species around the world are habituating to humans and human infrastructure, which can cause the loss of migratory behavior, local overpopulation, ecosystem damage, and human‐wildlife interactions. Wildlife managers sometimes attempt to reduce habituation by subjecting ungulates to aversive conditioning, comprised of negative stimuli in association with specific locations or behaviors, but high variability in the responsiveness of animals has limited the utility of this technique. We studied this limitation using 20 wild elk (Cervus canadensis) inhabiting a mountain town by identifying and comparing the responses of individuals categorized along a personality gradient from shy to bold, subjecting animals to aversive conditioning that either isolated animals or let them remain in a group, and then comparing their wariness via flight response distances before, during, and after conditioning. Bolder elk had significantly greater increases in wariness during conditioning and greater decreases in wariness once the conditioning period was complete. Isolation versus group‐based treatment did not affect responsiveness during the conditioning period, but isolated animals retained more wariness after conditioning ended. These results suggest that wildlife managers could increase the efficacy of aversive conditioning by identifying and targeting specific personality types and individuals to modify behavior and mitigate the broader ecological effects of habituated wildlife. © 2018 The Wildlife Society.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".