(Table 1) Age, fork length, and tissue d15N and element concentration of arctic char (Salvelinus alpinus) from Lake Hazen
Bibliographic record
Abstract
Arctic char (Salvelinus alpinus L.), the top predator in High Arctic lakes, often is used as a bioindicator of Hg contamination in Arctic aquatic ecosystems. The present study investigated effects of trophic position, size, and age of Arctic char in Lake Hazen, the largest lake in the Canadian High Arctic (81°50'N, 70°25'W), on Hg bioaccumulation. In addition, several essential (Se, K) and nonessential elements (Tl, Cs) in char muscle tissue were examined to compare their behavior to that of Hg. Trophic position of Arctic char was identified by stable isotope (d15N) signature. Temporal trends of Hg from seven sampling campaigns over a 16-year period (1990-2006) were investigated for the overall data and for one trophic class. Concentrations of Hg were not correlated with age but were positively related to fork length and trophic position. Large char with greater d15N signatures (>12 per mil) had larger Hg concentrations (0.09-1.63 µg/g wet wt) than small char with smaller d15N signatures (<12 per mil, 0.03-0.32 µg/g wet wt), indicating that Hg concentrations increased with trophic position. Nonessential Cs and Tl showed relationships to age, length, and trophic position similar to those of Hg, indicating their potential to bioaccumulate and biomagnify. Essential Se and K did not show these relationships. Concentrations of Hg were adjusted using d15N, leading to less within-year variability and a more consistent temporal trend. The d15N-adjusted trend showed no decline of Hg in Arctic char from Lake Hazen (1990-2006) in the overall data set and in the small morphotype. Trends for the same period before the adjustment were not significant for the overall data set, but a slight decrease was apparent in the small morphotype. The results confirm the need to consider trophic position and fish size when monitoring temporal trends of Hg, particularly for species with different morphotypes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.299 | 0.001 |
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; both teacher heads agree on what is shown here.
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".