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Record W2013460093 · doi:10.1139/z00-184

The effect of interspecific competition on habitat selection by voles: an experimental approach

2001· article· en· W2013460093 on OpenAlexvenueno aff
Yu-Teh K. Lin, George O. Batzli

Bibliographic record

VenueCanadian Journal of Zoology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersCampus Research Board
KeywordsMicrotusInterspecific competitionBiologyHabitatBiological dispersalCompetition (biology)EcologyPopulationDemography

Abstract

fetched live from OpenAlex

Both meadow voles (Microtus pennsylvanicus) and prairie voles (Microtus ochrogaster) prefer habitats with high vegetative cover, but in east-central Illinois, meadow voles tend to be associated with higher cover and prairie voles with lower cover. The competition hypothesis proposes that this pattern of habitat segregation reflects the effects of interspecific competition on habitat selection. To test this hypothesis we conducted field experiments that allowed the two species to select from among several habitats when alone and when together. We expected to find a lower proportion of each species in the habitat most associated with the other species, and a negative correlation between the demography and density of each species and the density of the competing species, but this was not the case. Inter specific competition did affect movement patterns of prairie voles. In the presence of meadow voles, net movement (immigration minus emigration) of prairie voles in high-cover habitats decreased and net dispersal of individuals from high- to low-cover habitats increased. Thus, our results indicated only a weak effect of competition on habitat selection. We suggest that other mechanisms, such as differences in habitat preference (or tolerance), differences in dispersal ability, and the advantage of first residency, need to be considered in conjunction with interspecific competition to explain the habitat segregation observed in these species.

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 score0.025
Threshold uncertainty score0.996

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)0.0000.000

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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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

Citations15
Published2001
Admission routes1
Has abstractyes

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