MétaCan
Menu
Back to cohort

Coyote prey selection and community stability during a decline in food supply

2005· article· en· W1983691513 on OpenAlexaff
Laura R. Prugh

Bibliographic record

VenueOikos · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation
KeywordsPredationForagingSnowshoe hareEcologyBiologyPopulationHabitatAbundance (ecology)PredatorOptimal foraging theory

Abstract

fetched live from OpenAlex

The foraging behavior of predators can have a large influence on community dynamics and has been shown to increase stability in some cases and decrease stability in others. I studied the foraging behavior of coyotes ( Canis latrans ) in the Alaska Range during the peak and decline of a snowshoe hare ( Lepus americanus ) population cycle (1999–2002). Coyote diet was compared with prey availability to test for changes in prey selection and to examine the effect of coyote predation on the vertebrate prey community. Coyotes responded to the hare decline by increasing selection for hares and porcupines, whereas selection for voles, ground squirrels and Dall sheep did not change. Although the study area was characterized by considerable habitat heterogeneity, coyotes utilized the area as a fine‐grained environment. Coyote foraging behavior was driven primarily by changes in snowshoe hare abundance, and their sensitivity to change in alternative prey density was low. Predation by coyotes may therefore decrease the stability of alternative prey populations rather than dampening fluctuations. In order for predation to enhance the stability of prey populations, I hypothesize that prey profitability must be determined primarily by abundance.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.949

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)0.0010.000

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 head0.014
GPT teacher head0.220
Teacher spread0.206 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations95
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueOikosSame topicWildlife Ecology and ConservationFrench-language works237,207