Harvester selection and observed mercury levels in Eastern Beaufort Sea and Western Hudson Bay beluga whales (Delphinapterus leucas)
Bibliographic record
Abstract
Mercury in marine biota has been extensively studied across Inuit Nunaat because it bioaccumulates and biomagnifies in high trophic level species, such as the beluga whale ( Delphinapterus leucas ), or qilalugaq in Inuktut. Qilalugaait (pl) are a staple in many coastal Inuit communities, including Tuktoyaktuk, Northwest Territories and Arviat, Nunavut. We examine how total mercury (THg) concentrations in two beluga populations are influenced by biased sampling resulting from local harvester preferences. We examined historical THg in skin, muscle, and liver (1980's to 2022) together with local qualitative interviews from two beluga-harvesting communities. Age and length bins were used to compare similar sized and aged whales between locations, where males (350 - 400 cm, and 20–30 years) and females (330–400 cm, and 15–30 years) were segregated. The interviews revealed distinct preferences whereby harvesters in Tuktoyaktuk actively sought larger (length) male whales, whereas harvesters in Arviat, selected wide and even range across size and sex. These local preferences were also evident in the historical dataset, with the median age and lengths were 31 years and 389.0 cm in Tuktoyaktuk ( n = 461) and 23 and 336.0 cm in Arviat ( n = 146). For males, mean and median THg concentrations were higher in beluga harvested from Tuktoyaktuk than Arviat in all three tissues with age and lengths combined, yet in the selected age and length bins, there was no difference in mean and median THg in the muscle tissue, and in median liver THg. There were significant differences in mean and median skin THg and in mean liver THg concentrations between males. In female whales, THg concentrations did not differ between Tuktoyaktuk and Arviat (in ages and lengths combined and in selected age bins across all tissues), excluding median muscle THg concentration. This study indicated that differences in THg concentrations that were previously observed resulted from hunter preferences in these two communities. • Mercury concentrations in two beluga populations were examined together with harvester interviews. • Both mercury dataset and interviews show clear harvest preferences between the two communities (size and sex difference). • Mercury concentrations are more similar between the Eastern Beaufort Sea and Western Hudson Bay than previously thought. • Local contexts and cultural difference should be considered as they may impact data interpretation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".