Toxicity of Salts, Metals, and Nitrogenous Contaminants to Cold-Water Fish Under Northern Conditions
Bibliographic record
Abstract
The goal of this thesis was to assess whether the current rainbow trout reference method used to ensure protection of native cold-water fish in Canada is adequately sensitive for application in northern environments. Comparative acute toxicity testing of seventeen inorganic contaminants found in mine effluents (CaCl2, MgCl2, KCl, NaCl, SO4 - , MoO4 2-, Al, As, Cd, Cr, Cu, Ni, Se, and Zn, NH3, NO2 - and NO3 -) was conducted using rainbow trout and five northern species of interest (arctic char, lake trout, lake whitefish, round whitefish, and arctic grayling) at three cold-water temperatures (5, 10, and 15°C); three water hardness levels (30, 60, and 120 mg CaCO3/L) for metals and metalloids; and 7 pH levels (pH 5.0, 5.5, 6.0, 6.5, iii 7.0, 7.5, 8.0) for NH3. The suite of assays produced 383 new 96-h LC50 values for juvenile cold-water fish. The ability of the reference species to protect other cold-water fish under dynamic conditions was assessed by comparing the 96-h rainbow trout LC50 for each contaminant reference conditions to the 96-h LC50 for each novel assay. To assess hazard to cold-water fish under existing or likely conditions, observed LC50s were used to calculate Hazard Quotients using available water quality guidelines and measured mine effluent concentrations. To assess the influence of test duration, acute LC50 values were calculated for mortalities observed at 24-, 48-, and 72-h of exposure for each assay, pooled, and assessed for trends in time required to achieve maximal toxic effect between species, contaminants, and water hardness level. The overall conclusion of this thesis is that rainbow trout are an adequate surrogate for cold-water fish species when environmental conditions are accounted for and an inter-species ecological safety factor of 10 applied. Some potential hazards under existing exposure conditions were identified, but only under spill or exceedance concentrations (effluents above regulatory limits) and not under current management levels. All species displayed similar trends in relation to time required to achieve maximal toxic effect, although many assays displayed continued mortality after 72-h, suggesting that the prescribed test length (96-h) may be underestimating toxicity and influencing the observation of acute effects.
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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 | 0.000 | 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) | 0.001 | 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".