Decreasing mercury concentrations in beaks of the giant warty squid Moroteuthopsis longimana in the Scotia Sea (Southern Ocean) since the 1970s
Bibliographic record
Abstract
The giant warty squid Moroteuthopsis longimana is an important prey of top predators in the Southern Ocean. It is therefore a major link in the pathway of contaminants like mercury (Hg) to higher levels in food webs. In this study, we evaluated changes in Hg concentrations in beaks of adult M. longimana collected from the boluses (pellets) of wandering albatross Diomedea exulans chicks at Bird Island (South Georgia) over five decades (1976, 1984, 1995, 2006 and 2016). A steep decrease in Hg concentrations was observed in M. longimana from 1984 to 1995 (0.086 ± 0.021 μg.g −1 to 0.017 ± 0.013 μg.g −1 ), with concentrations remaining low thereafter, likely reflecting the effects of international regulations and the global reductions in Hg emissions and usage initiated in the 1970s. Hg concentrations were not related to the squid size, δ 15 N nor δ 13 C values (proxies for trophic position and habitat, respectively), providing no evidence of bioaccumulation nor biomagnification in this squid species. Our results suggest that Hg concentrations in the beaks may be related to Hg bioavailability in the ecosystem, which makes M. longimana a potential biomonitor of Hg concentrations in pelagic environments of the Southern Ocean. However, further investigations are needed to confirm this finding.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".