Mercury in the marine environment of the Canadian Arctic: Review of recent findings
Bibliographic record
Abstract
This review summarizes data and information which have been generated on mercury (Hg) in the marine environment of the Canadian Arctic since the previous Canadian Arctic Contaminants Assessment Report (CACAR) was released in 2003. Much new information has been collected on Hg concentrations in marine water, snow and ice in the Canadian Arctic. The first measurements of methylation rates in Arctic seawater indicate that the water column is an important site for Hg methylation. Arctic marine waters were also found to be a substantial source of gaseous Hg to the atmosphere during the ice-free season. High Hg concentrations have been found in marine snow as a result of deposition following atmospheric mercury depletion events, although much of this Hg is photoreduced and re-emitted back to the atmosphere. The most extensive sampling of marine sediments in the Canadian Arctic was carried out in Hudson Bay where sediment total Hg (THg) concentrations were low compared with other marine regions in the circumpolar Arctic. Mass balance models have been developed to provide quantitative estimates of THg fluxes into and out of the Arctic Ocean and Hudson Bay. Several recent studies on Hg biomagnification have improved our understanding of trophic transfer of Hg through marine food webs. Over the past several decades, Hg concentrations have increased in some marine biota, while other populations showed no temporal change. Marine biota also exhibited considerable geographic variation in Hg concentrations with ringed seals, beluga and polar bears from the Beaufort Sea region having higher Hg concentrations compared with other parts of the Canadian Arctic. The drivers of these variable patterns of Hg bioaccumulation, both regionally and temporally, within the Canadian Arctic remain unclear. Further research is needed to identify the underlying processes including the interplay between biogeochemical and food web processes and climate change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".