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Record W2973744420 · doi:10.1111/oik.06351

Seasonality shapes the amplitude of vole population dynamics rather than generalist predators

2019· article· en· W2973744420 on OpenAlexaff
Harry P. Andreassen, Kaja Johnsen, Barbara Joncour, Magne Neby, Morten Odden

Bibliographic record

VenueOikos · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsQueen's University
FundersMattilsynetMiljødirektoratetNorges Forskningsråd
KeywordsGeneralist and specialist speciesVolePopulation cycleEcologyBiologyPredationPopulationBank voleSeasonalityHabitatDemography

Abstract

fetched live from OpenAlex

Seasonality has been suggested as a necessary factor for the initiation of vole population cycles in Fennoscandia. This has been well described for a latitudinal gradient. Here, we used an elevational gradient as a proxy for winter length to study how the length of the winter season correlates with the amplitude of bank vole Myodes glareolus population cycles. In addition, we studied whether the small mammalian generalist predator community present locally could explain any elevational effects. We estimated the population size of 30 local bank vole populations. We found a strong effect of elevation on the amplitude of the population cycle with local populations at around 800 m elevation having 1.5 times greater densities than populations in the valley (ca 300 m elevation). A univariate model with elevation as predictor for amplitude was twice as likely to be the best model than models including generalist predators. Our results fit well with the theories of a positive effect of winter length on the amplitude of vole population cycles in Fennoscandia, irrespective of whether the seasonal effect corresponds to a latitudinal or elevational gradient. The mechanisms may be limited resources during winter rather than generalist predators.

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 score0.002
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)0.0020.000

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 head0.012
GPT teacher head0.247
Teacher spread0.235 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

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