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Record W2792945534 · doi:10.1002/jwmg.21449

Personality influences wildlife responses to aversive conditioning

2018· article· en· W2792945534 on OpenAlexafffund
Rob Found, Colleen Cassady St. Clair

Bibliographic record

VenueJournal of Wildlife Management · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaParks CanadaAlberta Conservation Association
KeywordsConditioningHabituationWildlifePersonalityPsychologyUngulateCervus elaphusConditioned responseEcologySocial psychologyClassical conditioningBiologyHabitatNeuroscience

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.017
GPT teacher head0.263
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations39
Published2018
Admission routes2
Has abstractyes

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