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Record W2071695379 · doi:10.1021/es900471g

Sea Ice-associated Diet Change Increases the Levels of Chlorinated and Brominated Contaminants in Polar Bears

2009· article· en· W2071695379 on OpenAlexaff
Melissa A. McKinney, Elizabeth Peacock, Robert J. Letcher

Bibliographic record

VenueEnvironmental Science & Technology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsCarleton UniversityGovernment of Nunavut
Fundersnot available
KeywordsUrsus maritimusArcticEnvironmental scienceClimate changeSea iceBayEcosystemFood webEcologyMarine ecosystemPollutantOceanographyBiologyGeology

Abstract

fetched live from OpenAlex

Two global environmental issues, climate change and contamination by persistent organic pollutants, represent major concerns for arctic ecosystems. Yet, it is unclear how these two stressors interact in the Arctic. For instance, the influence of climate-associated changes in food web structure on exposure to pollutants within arctic ecosystems is presently unknown. Here, we report on recent changes in feeding ecology (1991-2007) in polar bears (Ursus maritimus) from the western Hudson Bay subpopulation that have resulted in increases in the tissue concentrations of several chlorinated and brominated contaminants. Differences in timing of the annual sea ice breakup explained a significant proportion of the diet variation among years. As expected from climate change predictions, this diet change was consistent with an increase in the consumed proportions of open water-associated seal species compared to ice-associated seal species in years of earlier sea ice breakup. Our results demonstrate that climate change is a modulating influence on contaminants in this polar bear subpopulation and may pose an additional and previously unidentified threat to northern ecosystems through altered exposures to contaminants.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.016
GPT teacher head0.232
Teacher spread0.215 · 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.

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

Citations138
Published2009
Admission routes1
Has abstractyes

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