Ionic aluminium concentrations exceed thresholds for aquatic health in Nova Scotian rivers, even during conditions of high dissolved organic carbon and low flow
Bibliographic record
Abstract
Acid deposition released large amounts of aluminium into streams and lakes during the last century in northern Europe and eastern North America. Elevated aluminium concentrations caused major environmental concern due to aluminium's toxicity to terrestrial and aquatic organisms and led to the extirpation of wild Atlantic salmon populations. Air pollution reduction legislation that began in the 1990s in North America and Europe successfully reduced acid deposition, and the aluminium problem was widely considered solved. However, accumulating evidence indicates that freshwater systems still show delays in recovery from acidification, with poorly understood implications for aluminium concentrations. Here, we investigate spatial and temporal patterns of labile cationic forms of aluminium (Al i ) from 2015 to 2018 in 10 catchments in Nova Scotia, Canada; this region was one of the hardest hit by acid deposition, although it was not considered to have an aluminium problem due to its high dissolved organic carbon (DOC) concentrations that were expected to reduce Al i concentrations. Surprisingly, our results show the widespread and frequent occurrences of Al i concentrations that exceed toxic thresholds in all sampled rivers despite high DOC concentrations. Generalized linear mixed model results reveal that DOC, instead of being inversely related to Al i , is the strongest predictor (positive) of Al i concentrations, suggesting that the recruitment properties of DOC in soils outweigh its protective properties in streams. Lastly, we find that, contrary to the common conceptualization that high Al i levels are associated with storm flow, high Al i concentrations are found during base flow. Our results demonstrate that elevated Al i concentrations in Nova Scotia continue to pose a threat to aquatic organisms, such as the biologically, economically, and culturally significant Atlantic salmon ( Salmo salar ).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".