Paleolimnological assessment of riverine and atmospheric pathways and sources of metal deposition at a floodplain lake (Slave River Delta, Northwest Territories, Canada)
Bibliographic record
Abstract
Growth of natural resource development in northern Canada has raised concerns about the effects on downstream aquatic ecosystems, but insufficient knowledge of pre-industrial baseline conditions continues to undermine ability of monitoring programs to distinguish industrial-derived contaminants from those supplied by natural processes. Here, we apply a novel paleolimnological approach to define pre-industrial baseline concentrations of 13 priority pollutant metals and vanadium and assess temporal changes, pathways and sources of these metals at a flood-prone lake (SD2) in the Slave River Delta (NWT, Canada) located ~500 km north of Alberta's oil sands development and ~140 km south of a former gold mine at Yellowknife, NWT. Results identify that metal concentrations, normalized to lithium concentration, are not elevated in sediments deposited during intervals of high flood influence or low flood influence since onset of oil sands development (post-1967) relative to the 1920-1967 baseline established at SD2. When compared to a previously defined baseline for the upstream Athabasca River, several metal-Li relations (Cd, Cr, Ni, Zn, V) in post-1967 sediments delivered by floodwaters appear to plot along a different trajectory, suggesting that the Peace and Slave River watersheds are important natural sources of metal deposition at the Slave River Delta. However, analysis revealed unusually high concentrations of As deposited during the 1950s, an interval of very low flood influence at SD2, which corresponded closely with emission history of the Giant Mine gold smelter indicating a legacy of far-field atmospheric pollution. Our study demonstrates the potential for paleolimnological characterization of baseline conditions and detection of pollution from multiple pathways in floodplain ecosystems, but that knowledge of paleohydrological conditions is essential for interpretation of contaminant profiles.
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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 | 0.001 | 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 | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".