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Record W2099995830 · doi:10.1139/z11-045

Impacts of generalist mesopredators on the demography of small-mammal populations in fragmented landscapes

2011· article· en· W2099995830 on OpenAlexvenueno aff
Timothy S. Eagan, James C. Beasley, Zachary H. Olson, Olin E. Rhodes

Bibliographic record

VenueCanadian Journal of Zoology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMesopredator release hypothesisGeneralist and specialist speciesBiologyApex predatorEcologyPeromyscusPredationTrophic levelAbundance (ecology)Deer mouseEcosystemPredatorIntraguild predationVulpesTrophic cascadeDefaunationHabitat

Abstract

fetched live from OpenAlex

A consequence of the reduction and subsequent fragmentation of native habitats has been the loss or severe reduction of specialist predator populations from these altered ecosystems, resulting in a “release” of generalist predators. Demographic aspects of small-rodent populations, especially predator-driven density cycles, have been extensively studied. However, the majority of studies examining predator–prey dynamics have been conducted in relatively undisturbed ecosystems, while more limited data are available for regions that have been greatly modified by human settlement. Using raccoons ( Procyon lotor (L., 1758)) and white-footed mice ( Peromyscus leucopus (Rafinesque, 1818)) as focal species, we used an experimental framework to evaluate the hypothesis that generalist mesopredators limit small-mammal abundance in landscapes that have been significantly altered by human land use. Both parametric and nonparametric analyses indicated that populations of white-footed mice exhibited a significant increase (32%) in density where raccoon abundance was reduced when compared with control populations. Our study highlights an important role that superabundant mesopredators can play in ecosystems through the limitation of secondary prey populations. This research suggests that further investigation of the trophic dynamics of agricultural ecosystems is critical if we are to elucidate the fundamental ecological mechanisms associated with the persistence of species in disturbed environments.

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 score0.520
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)0.0010.000

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 head0.045
GPT teacher head0.238
Teacher spread0.193 · 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

Citations16
Published2011
Admission routes1
Has abstractyes

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