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Record W2785431983 · doi:10.1139/as-2017-0049

Legacy contaminants in the eastern Beaufort Sea beluga whales (<i>Delphinapterus leucas</i>): are temporal trends reflecting regulations?

2018· article· en· W2785431983 on OpenAlexafffundvenue
Marie Noël, Lisa L. Loseto, Gary A. Stern

Bibliographic record

VenueArctic Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversity of ManitobaFisheries and Oceans Canada
FundersFisheries and Oceans CanadaFisheries Joint Management CommitteeUniversity of Winnipeg
KeywordsBeluga WhaleBlubberLeucasBelugaHexachlorobenzeneArcticEnvironmental scienceChlordaneDieldrinHeptachlorPersistent organic pollutantEstuaryOceanographyEnvironmental chemistryFisheryPollutantEcologyPesticideBiologyChemistryGeology

Abstract

fetched live from OpenAlex

Once deposited onto Arctic ecosystems, persistent organic pollutants (POPs) biomagnify in foodwebs such that relatively high levels have been detected in predators like beluga whales (Delphinapterus leucas). Our study aimed at assessing temporal trends of legacy POPs in eastern Beaufort Sea beluga blubber collected during traditional harvests in the Mackenzie Estuary area, Northwest Territories. Concentrations of polychlorinated biphenyls (PCBs) and 14 pesticides were quantified in 185 blubber samples collected between 1989 and 2015. The majority of legacy POPs analyzed showed no significant changes during the study period (ΣPCBs, Σchlordanes, Σdichlorodiphenyltrichloroethane, hexachlorobenzene, dieldrin, and mirex) and, therefore, did not reflect regulations put into place over the past decades. Although α- (82.6 ± 12.6 and 15.9 ± 1.9 ng/g in 1989 and 2015, respectively) and γ-hexachlorocyclohexane (γ-HCH) (126.6 ± 23.9 and 13.9 ± 0.9 ng/g, respectively) showed significant decrease between 1989 and 2015, β-HCH showed a more complex trend with concentrations increasing between 1989 (71.2 ± 13.4 ng/g) and 2004 (276.8 ± 13.5 ng/g) before decreasing until 2015 (174.7 ± 8.3 ng/g). Differences in trends likely reflect physico-chemical properties affecting transport to the Arctic. With climate change and melting sea ice potentially affecting the transport and release of legacy POPs, continuous monitoring is necessary.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0040.004
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.095
GPT teacher head0.401
Teacher spread0.306 · 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; both teacher heads agree on what is shown here.

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

Citations11
Published2018
Admission routes3
Has abstractyes

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