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Record W3035616444 · doi:10.1139/facets-2019-0056

Variation in isotopic niche, digestive tract morphology, and mercury concentrations in two sympatric waterfowl species wintering in Atlantic Canada

2020· article· en· W3035616444 on OpenAlexaffvenueabout
Matthew D. English, Gregory J. Robertson, Nelson J. O’Driscoll, Sara J. Klapstein, Liam E. Peck, Mark L. Mallory

Bibliographic record

VenueFACETS · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsEnvironment and Climate Change CanadaAcadia University
Fundersnot available
KeywordsAnasNicheEcological nicheSympatric speciationWaterfowlBiologyEcologyNiche segregationInterspecific competitionCompetition (biology)Niche differentiationHabitatZoology

Abstract

fetched live from OpenAlex

Sympatric communities of organisms may exploit different ecological niches to avoid intra- and interspecific competition. We examined the isotopic niches of American black ducks ( Anas rubripes) and mallards ( A. platyrhynchos) wintering in coastal and urban areas of Atlantic Canada and compared isotopic niche with digestive tract morphologies and blood mercury (Hg) concentrations. Isotopic niche width (for δ 13 C and δ 15 N) varied between the three groups of ducks studied, with coastally foraging black ducks exhibiting the widest isotopic niche, followed by coastal mallards, while urban feeding black ducks had a narrow isotopic niche. These niche differences had physical and chemical consequences: coastal black ducks had longer digestive tracts, a larger range in gizzard sizes, and higher and more variable Hg concentrations than urban black ducks and coastal mallards. This plasticity in ecological niche may reduce competition among and within species, and subsequently explain why winter numbers of black ducks and mallards have increased in Atlantic Canada.

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 score0.524
Threshold uncertainty score0.703

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 head0.010
GPT teacher head0.222
Teacher spread0.212 · 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

Citations5
Published2020
Admission routes3
Has abstractyes

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