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Record W2150427664 · doi:10.1139/er-2013-0059

Methylmercury biogeochemistry: a review with special reference to Arctic aquatic ecosystems

2014· review· en· W2150427664 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEnvironmental Reviews · 2014
Typereview
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Waterloo
FundersAlberta Innovates
KeywordsMethylmercuryBioaccumulationBiomagnificationEnvironmental chemistryMercury (programming language)ArcticBiogeochemistryAquatic ecosystemEcosystemEnvironmental scienceMarine ecosystemFood chainEcologyFood webChemistryBiology

Abstract

fetched live from OpenAlex

There has been increasing concern about mercury (Hg) levels in marine and freshwater organisms in the Arctic, due to the importance of traditional country foods such as fish and marine mammals to the diet of Northern Peoples. Due to its toxicity and ability to bioaccumulate and biomagnify in food webs, methylmercury (MeHg) is the form of Hg that is of greatest concern. The main sources of MeHg to Arctic aquatic ecosystems, the processes responsible for MeHg formation and degradation in the environment, MeHg bioaccumulation in Arctic biota and the human health implications for Northern Peoples are reviewed here. In Arctic marine ecosystems, Hg(II) methylation in the water column, rather than bottom sediments, is the primary source of MeHg, although a more quantitative understanding of the role of dimethylmercury (DMHg) as a MeHg source is needed. Because MeHg production in marine waters is limited by the availability of Hg(II), predicted increases in Hg(II) concentrations in oceans are likely to result in higher MeHg concentrations and increased exposure to Hg in humans and wildlife. In Arctic freshwaters, MeHg concentrations are a function of two antagonistic processes, net Hg(II) methylation in bottom sediments of ponds and lakes and MeHg photodemethylation in the water column. Hg(II) methylation is controlled by microbial activity and Hg(II) bioavailability, which in turn depend on interacting environmental factors (temperature, redox conditions, organic carbon, and sulfate) that induce nonlinear responses in MeHg production. Methylmercury bioaccumulation–biomagnification in Arctic aquatic food webs is a function of the MeHg reservoir in abiotic compartments, as well as ecological considerations such as food-chain length, growth rates, life-history characteristics, feeding behavior, and trophic interactions. Methylmercury concentrations in Arctic biota have increased significantly since the onset of the industrial age, and in some populations of fish, seabirds, and marine mammals toxicological thresholds are being exceeded. Due to the complex connection between Hg exposure and human health in Northern Peoples—arising from the dual role of country foods as both a potential Hg source and a nutritious, affordable food source with many physical and social health benefits—-reductions in anthropogenic Hg emissions are seen as the only viable long-term solution.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.044

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 head0.048
GPT teacher head0.316
Teacher spread0.268 · 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