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Record W2340151815 · doi:10.5038/2074-1235.43.2.1133

Update and Trends of Three Important Seabird Populations in the Western North Atlantic Using a Geographic Information System Approach

2015· article· en· W2340151815 on OpenAlexfundaboutno aff
Sabina I. Wilhelm, Joshua Mailhiot, Jillian Arany, John W. Chardine, Gregory J. Robertson, Pierre C. Ryan

Bibliographic record

VenueMarine ornithology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersDepartment of Environment and Conservation, Government of Newfoundland and Labrador
KeywordsSeabirdGeographyOrnithologyPredationApex predatorEcosystemFisheryEcologyOceanographyBiologyGeology

Abstract

fetched live from OpenAlex

The productive waters of Newfoundland, Canada, render this region host to nationally and globally important breeding seabird populations.This study updates estimates and trends of three major populations using a Geographic Information System (GIS) approach to estimate occupied areas of high-density breeding seabirds, correcting for slope.Our results show that the Common Murre Uria aalge breeding population on Funk Island remains the largest in the western North Atlantic at 472 259 SE 32 740 (CI 398 669-545 849) pairs and increased at a rate of +0.3% per year between 1972 and 2009.The Atlantic Puffin Fratercula arctica colony on Great Island, Witless Bay, increased between 1979 and 1994 and continues to host the largest population of this species in North America at 174 491 (CI 147 559-201 423) breeding pairs estimated in 2011; the population has stabilized and may be showing signs of decline.Finally, Leach's Storm-Petrel Oceanodroma leucorhoa breeding on Great Island, previously the second largest population in the western North Atlantic, has declined by 55% since 1979; it was estimated at 134 139 (CI 76,459) pairs in 2011, and is the lowest to date.Our GIS approach incorporated a 3D model to correct for slope of nesting areas; compared with traditional non-GIS techniques, this approach increased the estimated occupied area by 5%-10% for flat surfaces occupied by murres, by 16%-36% for moderate slopes occupied by storm-petrels, and by 40%-46% for steep slopes occupied by puffins.The application of newer tools such as high resolution satellite imagery and digital elevation models, coupled with GIS, are becoming more common and continue to improve the efficiency and accuracy of assessing occupied areas of highdensity breeding seabirds.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.052
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.027
GPT teacher head0.232
Teacher spread0.205 · 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.

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

Citations38
Published2015
Admission routes2
Has abstractyes

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