Recovery of Chironomidae from metal contamination in a multi-stressor environment: a paleolimnological analysis of a circumneutral Sudbury, Ontario lake
Bibliographic record
Abstract
Metal contamination and eutrophication of freshwater resources represent major threats to water-quality worldwide. Sudbury Ontario, the world’s second largest mining and smelting center, became severely contaminated before successful remediation efforts initiated in the 1970’s were able to restore aquatic and terrestrial environments. However, the individual impact of metal contamination in isolation from the effects of acidification on aquatic communities remains relatively unexplored. In the face of additional stressors, including cultural eutrophication and climate warming, the potential for aquatic communities to fully recover to pre-disturbance conditions as a result of reduced metal contamination is uncertain. Paleolimnological techniques were utilized to characterize the response of chironomid assemblages in circumneutral Lake Wabagashik to declining metal concentrations whilst experiencing a warmer and more productive environment. Geochemical analysis tracked declining Cu, Ni, Pb, Cd, As, Zn and Co concentrations since 1956. NIRS-inferred chlorophyll-a concentrations increased since 1951, consistent with that of an oligotrophic basin that has slowly eutrophied. The pre-remediation chironomid assemblage was comprised of oligotrophic and metal-tolerant taxa. Following emission reductions, the relative abundance of eutrophic and metal-sensitive taxa increased. In comparison to aquatic communities from other metal contaminated lakes, changes in the chironomid assemblage were relatively small, likely reflecting the suppression of aqueous metals and low bioavailability due to the circumneutral nature of Lake Wabagashik. The results of this study reveal that direct chemical measurements do not necessarily dictate biological responses and that toxicity arises from an interaction of contamination with the specific local conditions.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 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".