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Record W2105373205 · doi:10.1644/07-mamm-a-147r1.1

Spatial and Temporal Dynamics of Small Mammals at a Regional Scale in Canadian Boreal Forest

2008· article· en· W2105373205 on OpenAlexafffundabout
Jeff Bowman, R. Dean Phoenix, Alissa Sugar, F. Neil Dawson, George Holborn

Bibliographic record

VenueJournal of Mammalogy · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsMinistry of Natural Resources and Forestry
FundersMinistry of Natural Resources
KeywordsBiological dispersalEcologyBiologyAbundance (ecology)PredationInterspecific competitionSpatial ecologyPopulationBorealPeromyscusTaigaGeography

Abstract

fetched live from OpenAlex

Spatial synchrony is a common feature of mammalian population dynamics that appears to be caused by different processes in different systems. We sampled 60 sites across >900 km in northern and central Ontario, Canada, from 2001 to 2004 to assess spatial and temporal trends in abundance and population growth of small mammals. We tested alternative predictions for 3 causes of synchrony: dispersal, predation, and correlated environmental perturbations (the Moran effect). During 25,680 trap nights, Myodes gapperi, Tamias striatus, and Peromyscus maniculatus were the most commonly captured species. Populations of all 3 species fluctuated markedly during the 4 years of sampling, but fluctuations appeared to occur over a relatively small spatial extent (<200 km for all species). No pairwise combination of species exhibited positive interspecific synchrony, suggesting that nomadic predation was not synchronizing declines among species. Our data were most consistent with the dispersal hypothesis or a Moran effect caused through synchronous food crops.

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 score0.773
Threshold uncertainty score0.791

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 head0.018
GPT teacher head0.224
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

Citations14
Published2008
Admission routes3
Has abstractyes

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