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Record W2081282146 · doi:10.5558/tfc77661-4

Impact of an ice storm on resident bird populations in eastern North America

2001· article· en· W2081282146 on OpenAlexvenueaboutno aff
Jonatan Blais, Jean‐Pierre L. Savard, Jean Pierre Gauthier

Bibliographic record

VenueThe Forestry Chronicle · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsWoodpeckerEcologySturnusBiologyStarlingSparrowAbundance (ecology)GeographyHabitat

Abstract

fetched live from OpenAlex

The January 1998 ice storm was very dramatic, particularly in Québec, with five days of nearly non-stop freezing rain and temperatures below 0 °C. We compared results of Christmas Bird Counts (complete counts conducted during one day within a 12-km radius by volunteers in winter) conducted before (1997–1998) and after (1999) the storm in control areas (16 sites) and in affected areas (15 sites). Abundance ratios (after/before) were significantly higher in control versus affected sites for Rock Dove Columba livia, Mourning Dove Zenaida macroura, Hairy Woodpecker Picoides villosus, Blue Jay Cyanocitta cristata, Black-Capped Chickadee Parus atricapillus and House Sparrow Passer domesticus. Paired -t- tests also indicated that the abundance of Brown Creeper Certhia americana and Downy Woodpecker Picoides pubescens was lower in affected sites following the storm. Only European Starling Sturnus vulgaris abundance increased significantly in affected sites. Species found in open habitats that forage mostly on the ground were less affected by the storm than tree foragers were. The effect of the storm on bird populations was quite significant and increased frequency of such storms could have drastic consequences on bird populations in the long term. Key words: ice storm, birds, Christmas Bird Counts, winter survival, climate change

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 score0.196
Threshold uncertainty score0.395

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.020
GPT teacher head0.278
Teacher spread0.259 · 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

Citations7
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueThe Forestry ChronicleSame topicFire effects on ecosystemsFrench-language works237,207