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Record W4393935382 · doi:10.1139/facets-2023-0121

River influence on mercury bioaccumulation in the coastal food web of Eeyou Istchee, James Bay, Canada

2024· article· en· W4393935382 on OpenAlexafffundvenueabout
John Chételat, Joel P. Heath, Lucassie Arragutainaq, John Lameboy, Christine McClelland, Raymond Mickpegak

Bibliographic record

VenueFACETS · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsMakivik CorporationThe Arctic Eider SocietyCree Board of Health and Social Services of James BayEnvironment and Climate Change Canada
FundersNorthern Contaminants ProgramFisheries and Oceans CanadaCrown-Indigenous Relations and Northern Affairs CanadaEnvironment and Climate Change Canada
KeywordsBioaccumulationBayMercury (programming language)FisheryFood webEnvironmental scienceOceanographyGeographyEcologyGeologyBiologyComputer sciencePredation

Abstract

fetched live from OpenAlex

Spatial patterns of bioaccumulated mercury were evaluated in coastal marine food webs of east Hudson Bay and east James Bay in the boreal subarctic of Canada. Two marine species, blue mussels ( Mytilus edulis) and common eider ducks ( Somateria mollissima) that consume mussels, were collected by a regional community-based monitoring network established in five communities. Stable isotope tracers (carbon, nitrogen, sulfur, and mercury) were measured to evaluate environmental drivers of mercury spatial patterns. Mercury concentrations of blue mussels and common eiders were twofold and fivefold higher, respectively, on the James Bay coast near the community of Chisasibi compared to sites in east Hudson Bay. Liver and muscle mercury concentrations of eiders from James Bay are among the highest values reported for the circumpolar subarctic and Arctic. Multiple lines of evidence (mercury spatial patterns, crustal elements in blue mussels, and mercury isotope values of common eiders) suggest elevated mercury in the coastal food web of east James Bay may be due to mercury loading from the La Grande River, which drains one of the largest hydroelectric developments in the world. These findings highlight the importance of further research on environmental processes linking large rivers to mercury bioaccumulation in northern coastal food webs.

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 score0.355
Threshold uncertainty score0.930

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 head0.017
GPT teacher head0.256
Teacher spread0.239 · 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

Citations3
Published2024
Admission routes4
Has abstractyes

Explore more

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