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Record W2005326532 · doi:10.1676/10-097.1

Arctic Foxes, Lemmings, and Canada Goose Nest Survival at Cape Churchill, Manitoba

2011· article· en· W2005326532 on OpenAlexaboutno aff
Matthew E. Reiter, David E. Andersen

Bibliographic record

VenueThe Wilson Journal of Ornithology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNest (protein structural motif)LagopusArctic foxGooseOccupancyEcologyArcticPredationAnatidaeAbundance (ecology)GeographyBiologyBranta

Abstract

fetched live from OpenAlex

We examined factors influencing Canada Goose (Branta canadensis interior) annual nest success, including the relative abundance of collared lemmings (Dicrostonyx richardsoni), arctic fox (Alopex lagopus) den occupancy, nest density, and spring phenology using data collected during annual Canada Goose breeding area surveys at Cape Churchill, Manitoba. Nest density and arctic fox den occupancy strongly influenced Canada Goose nest success. High nest density resulted in higher nest success and high den occupancy reduced nest success. Nest success was not influenced by lemming abundance in the current or previous year as predicted by the “bird-lemming” hypothesis. Reducing arctic fox abundance through targeted management increased nest survival of Canada Geese; a result that further emphasizes the importance of arctic fox as nest predators in this system. The spatial distribution of nest predators, at least for dispersed-nesting geese, may be most important for nest survival, regardless of the abundance of small mammals in the local ecosystem. Further understanding of the factors influencing the magnitude and variance in arctic fox abundance in this region, and the spatial scale at which these factors are realized, is necessary to fully explain predator-prey-alternative prey dynamics in this system.

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 score0.640
Threshold uncertainty score1.000

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)0.0010.000

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 head0.025
GPT teacher head0.202
Teacher spread0.178 · 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

Citations25
Published2011
Admission routes1
Has abstractyes

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