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Record W3096291956 · doi:10.3390/app10217556

Mercury in Marine Mussels from the St. Lawrence Estuary and Gulf (Canada): A Mussel Watch Survey Revisited after 40 Years

2020· article· en· W3096291956 on OpenAlexaboutno aff
Daniel Cossa, Anne-Marie Tabard

Bibliographic record

VenueApplied Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMusselEstuaryMytilusMercury (programming language)Dry weightFisheryEnvironmental chemistryWet weightBivalviaMolluscaEnvironmental scienceOceanographyBiologyEcologyChemistryGeology

Abstract

fetched live from OpenAlex

Various species of marine mussels have been used, in the last 50 years, as sentinel organisms for monitoring metal contamination along marine coasts. There are two main reasons for this: these mollusks concentrate metals in their soft tissue and they are geographically widespread. In practice, trace metal concentrations in mussel soft tissue reveal (after some correction for biotic effects) the contamination level of their surrounding environment. We present the results of a mercury (Hg) survey in Mytilus spp. collected in the summers of 2016, 2018, and 2019 at 51 stations distributed along the coasts of the Estuary and Gulf of St. Lawrence. Mercury concentrations ranged from 0.063 to 0.507 µg g−1 (dry weight, dw), with a grand mean of 0.173 ± 0.076 µg g−1 dw (±1 standard deviation), and a median of 0.156 µg g−1 dw for the 504 individuals analyzed. Mercury contents per individual mussel were significantly (p < 0.01) related to shell length and dry tissue weight, with the smaller individuals having the highest Hg concentrations. To take into account these biotic effects, we normalized Hg concentrations of the mussel soft tissue for constant shell length (L) and soft tissue weight (TW) based on the log-log relationships between Hg content and L or TW. The normalized Hg contents of mussels varied from 10.9 to 66.6 ng per virtual individual of 35 mm length and 0.17 g dry weight. A similar normalization procedure applied to 1977–1979 data, yielded a very similar range: 12 to 64 ng. This observation suggests that the Hg bioavailable to marine mussels in the study area did not change over a span of 40 years. Regional Hg distribution patterns indicate a gradual decrease of Hg content in mussels downstream from freshwater discharges to the St. Lawrence Estuary and the Baie des Chaleurs, suggesting that rivers constitute a significant Hg source in these estuarine systems. Atmospheric Hg deposition and concentration in marine waters of the Atlantic Ocean are known to have decreased in the last decades. However, in coastal environments, the response to these changes does not seem to be rapid, probably because of the long residence time of Hg in soils before being exported to coastal areas.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
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
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.234
Teacher spread0.211 · 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

Citations21
Published2020
Admission routes1
Has abstractyes

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