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Record W4200498893 · doi:10.1111/oik.08628

Predators reduce niche overlap between sympatric prey

2021· article· en· W4200498893 on OpenAlexaff
Justin A. Dellinger, Carolyn R. Shores, Apryle D. Craig, Shannon Kachel, Michael R. Heithaus, William J. Ripple, Aaron J. Wirsing

Bibliographic record

VenueOikos · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMinistry of Forests
Fundersnot available
KeywordsOdocoileusPredationSympatric speciationEcologyNichePredatorCanisBiologyGray wolfRange (aeronautics)SympatryNiche differentiationGeography

Abstract

fetched live from OpenAlex

Predators may alter niche overlap between prey species by eliciting divergent anti‐predator behavior. Accordingly, we exploited heterogeneous gray wolf Canis lupus presence in Washington, USA, to contrast patterns of resource and dietary overlap between mule Odocoileus hemionus and white‐tailed deer O. virginianus at sites with and without resident packs. Mule deer run (stot) in a way that is less effective as a means of fleeing from predators than the galloping gait of white‐tailed deer. Consequently, mule deer manage risk from coursing predators like wolves by avoiding encounters, whereas white‐tailed deer respond to such predators by exploiting areas where they are most likely to escape pursuit. Thus, under the ‘refuge partitioning hypothesis' whereby predators reduce prey niche overlap by eliciting use of different refugia, we predicted wolf exposure to 1) decrease resource and dietary overlap between these ungulates, and 2) induce segregation consistent with each species using different parts of the landscape to reduce their wolf risk. At the home range scale, the ways in which resource overlap diminished in the wolf areas were consistent with the prey species reducing their respective risks, particularly with respect to slope, with mule deer separating from white‐tailed deer by seeking steeper areas where wolf encounters are less likely. At the within‐home range scale, the manner in which spatial overlap decreased in relation to forest cover was consistent with species‐specific risk management, with mule deer avoiding wolf encounters by shifting toward this resource. Reduced resource overlap between the deer in areas occupied by wolves did not correspond with dietary divergence. Our findings suggest that wolf risk mediates spatial but not necessarily dietary overlap between sympatric ungulates, divergent anti‐predator behavior is a non‐consumptive pathway by which predators can reduce interspecific competition among prey, and use of disparate refugia by prey may not result in dietary divergence.

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 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 score0.015
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)0.0030.001

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 head0.014
GPT teacher head0.234
Teacher spread0.220 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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