Relationship between Mercury Concentration and Growth Rates for Walleyes, Northern Pike, and Lake Trout from Quebec Lakes
Bibliographic record
Abstract
Abstract The relationship between mercury (Hg) concentrations in fish muscle and fish growth rates was assessed for 54 walleye Sander vitreus , 52 northern pike Esox lucius , and 35 lake trout Salvelinus namaycush populations throughout the Province of Quebec, Canada. We used the von Bertalanffy growth model to estimate the ages of fish specimens for a given length, and Hg concentrations in fish specimens at standardized length were determined via a quadratic regression model. Measured values of Hg concentrations in walleyes, northern pike, and lake trout were then correlated to the estimated age at standardized length for each population (375, 675, and 550 mm, respectively). A model‐II regression was performed to describe the existing relationships. Growth rates were positively related to Hg concentrations in walleyes and northern pike (when three outliers were excluded), whereas no correlation was observed for lake trout. Our findings demonstrate that slower‐growing walleyes and northern pike have higher Hg concentrations at standardized length. For these fish species, growth rate could be used as an integrated proxy to predict Hg concentration in fish muscle on a regional scale. Our findings support the contention that biodilution can be an important factor regulating mercury concentrations in fish. Thus, our findings suggest that proper control of fish growth rate through fishing pressure, lake ecology, and watershed management could be used by fisheries management authorities to minimize the toxic risk associated with Hg exposure from fish consumption.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".