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Record W4385733820 · doi:10.1139/facets-2022-0232

Dynamic vegetation cover and decline in common eider breeding numbers in Nova Scotia, Canada

2023· article· en· W4385733820 on OpenAlexafffundvenueabout
Molly D. Tomlik, G. Randy Milton, Glen J. Parsons, Mark L. Mallory

Bibliographic record

VenueFACETS · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsAcadia University
FundersCanada Research Chairs
KeywordsEiderHabitatEcologyGeographyVegetation (pathology)CormorantNest (protein structural motif)PopulationPredationPopulation declineRange (aeronautics)BiologyDemography

Abstract

fetched live from OpenAlex

The American common eider ( Somateria mollissima dresseri) is a colonially nesting sea duck breeding on islands in the coastal regions of Atlantic Canada. Declines in colony size have been pronounced in some parts of its range, notably in Nova Scotia, and may be attributable to a variety of interconnected factors including changes in habitat conditions. Using surveys collected two decades apart, we compared nesting habitat types, availability, and use by breeding eiders on 16 islands that supported >1600 eider nests in 1992–1993, but 830 nests in 2013. While general patterns of eider nesting habitat use remained consistent (e.g., nesting preferences exhibited for Low Shrubland and Grassland habitats, and avoidance of forest or beach habitats), overall vegetation cover declined, but relative habitat changes were inconsistent across islands. Three of the islands with the greatest change in vegetation had cormorant ( Phalacrocorax spp.) colonies in 2013 that were not there in the earlier years. We suggest that changes in vegetation, in some cases facilitated by cormorant colony formation, influenced susceptibility of nesting females to predators, and these interconnected factors may be contributing to local population declines.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.653

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 studies0.0000.000
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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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

Citations2
Published2023
Admission routes4
Has abstractyes

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