Erosion of the Alberta badlands produces highly variable and elevated heavy metal concentrations in the Red Deer River, Alberta
Bibliographic record
Abstract
Erosion is important in the transport of heavy metals from terrestrial to fluvial environments. In this study, we investigated riverine heavy metal (Cd, Cu, Hg and Pb) dynamics in the Red Deer River (RDR) watershed at sites upstream (n = 2) and downstream (n = 7) of the Alberta badlands, an area of naturally high erosion. At sites draining the badlands, total water column Cd, Cu, Hg and Pb concentrations frequently exceeded guidelines for the protection of freshwater biota. Furthermore, peak concentrations of total Cd (9.8 μg L− 1), Cu (212 μg L− 1), Hg (649 ng L− 1) and Pb (361 μg L− 1) were higher than, or comparable to, values reported for rivers and streams heavily impacted by anthropogenic activities. Total suspended solids (TSS) explained a large proportion (r2 = 0.34–0.83) of the variation in total metal concentrations in the RDR and tributaries and metal fluxes were dominated by the particulate fraction (60–98%). Suspended sediment concentrations (Csed) and metal to aluminum ratios were generally not indicative of substantial sediment enrichment. Rather, the highly variable and elevated metal concentrations in the RDR watershed were a function of the high and variable suspended sediment fluxes which characterize the river system. While the impact of this on aquatic biota requires further investigation, we suggest erosion in the Alberta badlands may be contributing to Hg-based fish consumption advisories in the RDR. Importantly, this highlights a broader need for information on contaminant dynamics in watersheds subject to elevated rates of erosion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".