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Record W4403667379 · doi:10.22621/cfn.v137i4.3041

Retrospective comparison of the distribution and abundance of breeding Prairie Warbler (<i>Setophaga discolor</i>) along eastern Georgian Bay, Ontario, Canada

2024· article· en· W4403667379 on OpenAlexvenueaboutno aff
Kevin C. Hannah, David D. Hope, Elyse Howat, Christoph S. Ng, Rich Russell, Nora C. Spencer, Russ C. Weeber

Bibliographic record

VenueThe Canadian Field-Naturalist · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsWarblerBayGeorgianGeographyAbundance (ecology)Distribution (mathematics)EcologyForestryBiologyArchaeologyHabitat

Abstract

fetched live from OpenAlex

Species inhabiting rare habitats or unique geographic regions may be underrepresented in standard surveys. More intensive, periodic surveys may be required to improve data quality, especially for species of conservation concern. Prairie Warbler (Setophaga discolor) has experienced range-wide declines of >50% in recent decades and is a species of conservation concern in Canada. The largest continually occupied breeding population of this species in Canada occurs along the shoreline of eastern Georgian Bay, Ontario, where annual Breeding Bird Survey and eBird coverage is generally poor. In 2015, we replicated a spatially intensive 1997 survey of this species along the eastern shore of Georgian Bay, visiting the same sites and using comparable methods. We detected more male birds at the survey sites in 2015 (estimated >350 breeding pairs) than in 1997 (estimated 265 breeding pairs). We also surveyed sites farther north than those covered in 1997, but the breeding range appears not to have moved substantially northward. We also conducted additional surveys and canoe transects in the core range in southern Georgian Bay to ensure that breeding birds were not being missed. Combining data from all our surveys in 2015, we estimated a total of 427 singing males in eastern Georgian Bay. Although overall numbers here appear to have increased in recent decades, localized declines in some areas warrant further investigation. The population appears to be stable or increasing in this region, but we recommend intensively re-surveying this population on at least a 20-year basis.

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 score0.037
Threshold uncertainty score0.074

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.009
GPT teacher head0.205
Teacher spread0.196 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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