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Record W4226377900 · doi:10.1093/beheco/arac041

Hierarchy of fear: experimentally testing ungulate reactions to lion, African wild dog and cheetah

2022· article· en· W4226377900 on OpenAlexaff
Noa Rigoudy, Michael Clinchy, Mike Peel, Sarah E. Huebner, Craig Packer, Liana Zanette

Bibliographic record

VenueBehavioral Ecology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsWestern University
FundersÉcole Normale Supérieure de Lyon
KeywordsPantheraAcinonyx jubatusUngulateCarnivorePredationCrocuta crocutaBiologyEcologyPopulationPredatorZoologyHabitatDemography

Abstract

fetched live from OpenAlex

Abstract Experiments have begun demonstrating that the fear (antipredator behavioral responses) large carnivores inspire in ungulates can shape ecosystem structure and function. Most such experiments have focused on the impacts of either just one large carnivore, or all as a whole, rather than the different impacts different large carnivores may have in intact multi-predator-prey systems. Experimentally testing the relative fearfulness ungulates demonstrate toward different large carnivores is a necessary first step in addressing these likely differing impacts. We tested the fearfulness ungulates demonstrated to playbacks of lion (Panthera leo), African wild dog (Lycaon pictus), cheetah (Acinonyx jubatus) or non-predator control (bird) vocalizations, in Greater Kruger National Park, South Africa. Ungulates ran most to lions, then wild dogs, and then cheetahs, demonstrating a very clear hierarchy of fear. Those that did not run looked toward the sound more on hearing large carnivores than controls, looking most on hearing lions. Notably, prey species-specific population level kill rates by each predator did not predict the patterns observed. Our results demonstrate that different large carnivores inspire different levels of fear in their ungulate prey, pointing to differing community-level impacts, which we discuss in relation to the ongoing worldwide decline and loss of large carnivores.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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.

Opus teacher head0.028
GPT teacher head0.277
Teacher spread0.248 · 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; a candidate call from one teacher head, not a consensus.

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

Citations20
Published2022
Admission routes1
Has abstractyes

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