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Temporal trends of mercury in Arctic biota: 10 more years of progress in Arctic monitoring

2022· article· en· W4280528728 on OpenAlexafffund
Adam D. Morris, Simon Wilson, R. J. Fryer, Philippe J. Thomas, Karista Hudelson, Birgitta Andreasen, Pierre Blévin, Paco Bustamante, Olivier Chastel, Guttorm Christensen, Runé Dietz, Marlene S. Evans, Anita Evenset, Steven H. Ferguson, Jérôme Fort, Mary Gamberg, David Grémillet, Magali Houde, Robert J. Letcher, Lisa L. Loseto, Derek C. G. Muir, Marianna Pinzone, Amanda Poste, Heli Routti, Christian Sonne, Gary Stern, Frank F. Rigét

Bibliographic record

VenueThe Science of The Total Environment · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsBell (Canada)Fisheries and Oceans CanadaEnvironment and Climate Change Canada
FundersFondation BNP ParibasAgence Nationale de la RechercheCrown-Indigenous Relations and Northern Affairs CanadaInstitute for Clinical Evaluative SciencesBNP Paribas CardifNorsk PolarinstituttFisheries and Oceans CanadaEuropean CommissionEnvironment and Climate Change CanadaInstitut Polaire Français Paul Emile VictorMinistry of Education, IndiaKlima- og miljødepartementetNorges Forskningsråd
KeywordsBiotaArcticMercury (programming language)Environmental scienceSubarctic climateThe arcticPhysical geographyEcologyGeographyOceanographyFisheryGeologyBiologyComputer science

Abstract

fetched live from OpenAlex

Temporal trend analysis of (total) mercury (THg) concentrations in Arctic biota were assessed as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) Mercury Assessment. A mixed model including an evaluation of non-linear trends was applied to 110 time series of THg concentrations from Arctic and Subarctic biota. Temporal trends were calculated for full time series (6-46 years) and evaluated with a particular focus on recent trends over the last 20 years. Three policy-relevant questions were addressed: (1) What time series for THg concentrations in Arctic biota are currently available? (2) Are THg concentrations changing over time in biota from the Arctic? (3) Are there spatial patterns in THg trends in biota from the Arctic? Few geographical patterns of recent trends in THg concentrations were observed; however, those in marine mammals tended to be increasing at more easterly longitudes, and those of seabirds tended to be increasing in the Northeast Atlantic; these should be interpreted with caution as geographic coverage remains variable. Trends of THg in freshwater fish were equally increasing and decreasing or non-significant while those in marine fish and mussels were non-significant or increasing. The statistical power to detect trends was greatly improved compared to the 2011 AMAP Mercury Assessment; 70% of the time series could detect a 5% annual change at the 5% significance level with power ≥ 80%, while in 2011 only 19% met these criteria. Extending existing time series, and availability of new, powerful time series contributed to these improvements, highlighting the need for annual monitoring, particularly given the spatial and temporal information needed to support initiatives such as the Minamata Convention on Mercury. Collecting the same species/tissues across different locations is recommended. Extended time series from Alaska and new data from Russia are also needed to better establish circumarctic patterns of temporal trends.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.067
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.017
GPT teacher head0.260
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), 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

Citations44
Published2022
Admission routes2
Has abstractyes

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