Calcium and sodium as regulators of the recovery of four Daphnia species along a gradient of metal and base cations in metal contaminated lakes in Sudbury, Ontario, Canada
Bibliographic record
Abstract
Smelting of sulphur-rich metallic ores in Sudbury, Ontario, Canada, has caused acidification and metal contamination of thousands of lakes in the region. Recent reductions in smelter emissions have resulted in much ecological recovery, but the recovery of Daphnia species has been poor. To determine if Cu and Ni toxicity could explain differences in daphniid recovery among lakes, we compared results of 14 d static with renewal bioassays in waters from Blue Chalk Lake, an uncontaminated reference lake 200 km from Sudbury, and from five Sudbury lakes ranging in distance from the smelters and varying in metal and cation concentrations. We spiked Blue Chalk Lake water with Cu and Ni to levels resembling those of the Sudbury lakes and also tested the lake waters for toxicity. Survival of Daphnia pulex, D. pulicaria and D. mendotae decreased monotonically with increasing metal concentrations in the spiked Blue Chalk Lake treatments, falling from 90% in the controls to 0% at the two highest Cu and Ni levels, reflecting levels of Middle and Hannah lakes. In contrast, survival in waters collected from the actual Sudbury lakes did not monotonically track their total metal concentrations. Rather, survival fell to 0% in Clearwater Lake water, a lake with intermediate metal contamination (8.9 and 79.9 μg L–1 of Cu and Ni, respectively) vs 70-100% in the other lakes. We performed an additional assay with Clearwater Lake waters increasing its Ca and Na concentrations, singly and in combination to levels that reflected the levels in Middle Lake. The survival of the four daphniid species increased from 0% up to 80-100% with added Ca and from 0% to 60-90% with added Na. Lipid-ovarian indices had a similar trend to survival for D. mendotae and D. pulicaria in Bioassay 1, varying with the cation concentrations in the lakes for the daphniids in Bioassay 2. The bioassays results imply that regional recovery patterns of daphniids in Sudbury lakes cannot be understood without as a minimum considering both metal and base cation concentration differences among lakes, and give an indication of differences among Daphnia species to cope with metal stress.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".