Geochemical and biological controls on the ecological relevance of total, dissolved, and colloidal forms of trace elements in large boreal rivers: review and case studies
Bibliographic record
Abstract
The concentrations of trace elements (TEs) in large boreal rivers can fluctuate markedly due to changing water levels and flow rates associated with spring melt and variable contributions from tributaries and groundwaters, themselves having different compositions. These fluctuating and frequently high concentrations create regulatory challenges for protecting aquatic life. For example, water quality criteria do not account for changes in flow regimes that can result in TE levels that may exceed regulatory limits, and neither do they account for the markedly different lability and bioaccessibility of suspended solids. This review addresses the geochemical and biological processes that govern the lability and bioaccessibility of TEs in boreal rivers, with an emphasis on the challenges posed by the colloidal behaviour of many TEs, and their relationship to the dissolved fraction (i.e., <0.45 μm in size). After reviewing the processes and dynamics that give rise to the forms and behaviour of TEs in large boreal rivers, their relevance for aquatic organisms and the associated relationships between size and lability and bioaccessibility are discussed. The importance of biological variables and different forms of TEs for limiting lability and bioaccessibility are also addressed. Two case studies emphasize seasonal fluctuations and accompanying changes in the distribution of TE amongst different size fractions and associated colloidal species in large boreal rivers: the Northern Dvina and one of its tributaries, the Pinega River, both in Russia, and the Athabasca River in Alberta, Canada. Water quality in the Athabasca River is briefly discussed with respect to Canadian guidelines.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".