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Record W1991970795 · doi:10.1675/063.034.0203

Nesting Habitat Selection and Hatching Success of Whimbrels Near Churchill, Manitoba, Canada

2011· article· en· W1991970795 on OpenAlexafffundabout
Kate Ballantyne, Erica Nol

Bibliographic record

VenueWaterbirds · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of CanadaChurchill Northern Studies Centre
KeywordsGraminoidHabitatEcologyVegetation (pathology)ShrubNest (protein structural motif)LichenGeographyEcological successionBiologyPlant community

Abstract

fetched live from OpenAlex

The Whimbrel (Numenius phaeopus) is one of a suite of sub-arctic- and arctic-nesting shorebirds for which encroachment of woody vegetation into previously open habitats may cause a reduction in breeding habitat. Whimbrel nesting habitat selection was studied at two spatial scales near Churchill, Manitoba, Canada, to determine habitat preferences and the degree to which the species avoided woody vegetation. Whimbrels occupied sites at the mesohabitat (territory) scale characterized by either high lichen cover, or high graminoid and standing water cover. No Whimbrels nested in mesohabitat with >17.5% tall shrub cover, and only one pair nested where >38 trees existed within 30 m of the nest. At the microhabitat (nest) scale, Whimbrels nested in two distinct habitats. In lichen-dominated sites, nests had less concealing vegetation than unused sites whereas in graminoid dominated habitats, nests were more concealed than unused sites. Sixty-eight percent of nests were on hummocks or lichen ridges. Hatching success was not predicted by habitat characteristics and was lower than previously reported (2007: 26%; 2008: 14%). Avoidance of woody vegetation by breeding Whimbrels suggests that shrub and tree encroachment would reduce habitat availability in the Churchill region.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.013
GPT teacher head0.176
Teacher spread0.163 · 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 source (direct Gemma or distilled Codex), 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

Citations27
Published2011
Admission routes3
Has abstractyes

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