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Habitat selection and the scale of ghostly coexistence among Arctic rodents

2011· article· en· W2168881812 on OpenAlexaboutno aff
Som B. Ale, Douglas W. Morris, Angélique Dupuch, Debra E. Moore

Bibliographic record

VenueOikos · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTundraHabitatEcologyGeneralist and specialist speciesArcticCompetition (biology)Abundance (ecology)NicheBiologyGeography

Abstract

fetched live from OpenAlex

Competition between coexisting species existing near their stable equilibrium can be obscured if they occupy separate habitats. Theories of habitat selection promise an ability to reveal the underlying ghost of competition by using isodars to infer the behavioural map of habitat selection. We tested the theory with two years of data on abundance and habitat preference by three Arctic rodent species living at low density along a gradient of wet to dry tundra on Herschel Island in Canada's western Arctic. Generalist brown lemmings exhibited a constant partial preference toward wet tundra whereas specialist collared lemmings and voles occupied the driest and wettest zones respectively. Although both lemming species compete for habitats elsewhere in the Canadian Arctic, isodar analyses suggest that the three species occupy wet and dry habitats independently of one another on Herschel Island. Competition at this large scale may be hidden at low densities, however, if the wet‐dry dichotomy is too coarse. Analyses at a finer subdivision of habitat revealed that these species coexist by using different microhabitats. Collared lemmings shifted their niche towards even drier habitat as the abundance of brown lemmings increased. We were thus able to reveal the ghost of competition lurking at large scales through a more refined analysis at smaller scales of density‐dependent habitat use.

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 score0.007
Threshold uncertainty score0.492

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 studies0.0000.001
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 head0.018
GPT teacher head0.226
Teacher spread0.208 · 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

Citations25
Published2011
Admission routes1
Has abstractyes

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