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Record W3136687868 · doi:10.17630/sta/945

Mercury accumulation in the food web of the Scotia Sea, Southern Ocean

2020· dissertation· en· W3136687868 on OpenAlexaboutno aff
José Seco

Bibliographic record

VenueSt Andrews Research Repository (St Andrews Research Repository) · 2020
Typedissertation
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMercury (programming language)OceanographyFood webNova scotiaEnvironmental scienceFisheryGeographyGeologyBiologyEcologyComputer scienceEcosystem

Abstract

fetched live from OpenAlex

The aim of the work presented in this thesis was to understand processes of bioaccumulation and biomagnification of mercury (Hg) in a Southern Ocean (SO) food web, and to evaluate the effect of organism size and habitat in Hg accumulation during the last decade. To do this, tissues of various species occupying different trophic levels were analysed in samples collected over various sampling years (2006/07 and 2016/17) from areas with distinctive environmental characteristics. Different accumulation patterns were found: Antarctic krill juveniles had higher Hg concentrations than adults; in squid, Hg concentration increased with individual size in one species (Alluroteuthis antarcticus), decreased in another (Galiteuthis glacialis), and in another still, there was no obvious relationship (Bathyteuthis abyssicola); for myctophid fish there was a consistent increase of Hg concentration with fish size, with the exception of Electrona antarctica females. Proportions of organic Hg also varied between trophic groups, from relatively low (15-37%) in krill to virtual 100% in all myctophid tissues. Regarding Hg tissue allocation, squid muscle was the tissue that had highest Hg, followed by digestive gland and gills. Myctophids’ Hg concentrations were higher in the liver and heart than in muscle or gills. Geographic differences in Hg concentration in krill were found, with individuals from the South Orkney having Hg levels 5 to 7 times higher than South Georgia: this geographic variation was not found in myctophids. As expected, when evaluating Hg along the food web, POM spell out had the lowest Hg levels, followed in increasing concentration by zooplankton, squid, myctophid, notothenid fish and seabirds. Predators exhibited variability in Hg levels which corresponding to the trophic level of their diets, with lower G15N levels corresponding to lower Hg concentrations. The mid food web groups (squid and myctophids) showed a decreasing trend in Hg level over the last decade, but that difference was not reflected in top predators, for which Hg levels were higher in 2016/17 than in 2007/08. This difference between years may be due to a decrease in the abundance of krill that year, which would have necessitated a change by krill predators to myctophids, a higher Hg body burden prey. This thesis revealed details of Hg contamination in SO biota, emphasizing the role of atmospheric transportation in global mercury contamination. Present-day regional warming may lead to increasing Hg availability in the SO as glacial melt is releasing contaminants previously trapped following atmospheric precipitation. Climate change, pollution and growing fishing pressure are together placing increased pressure on SO marine ecosystems and the living resources they contain.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.313
Threshold uncertainty score0.622

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.085
GPT teacher head0.373
Teacher spread0.288 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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