Use of pre-industrial floodplain lake sediments to establish baseline river metal concentrations downstream of Alberta oil sands: a new approach for detecting pollution of rivers
Bibliographic record
Abstract
In the Alberta oil sands region, insufficient knowledge of pre-disturbance reference conditions has undermined the ability of the Regional Aquatics Monitoring Program (RAMP) to detect pollution of the Athabasca River, because sampling began three decades after the industry started and the river naturally erodes oil-bearing strata. Here, we apply a novel approach to characterize pre-industrial reference metal concentrations in river sediment downstream of Alberta oil sands development by analyzing metal concentrations in sediments deposited in floodplain lakes of the Athabasca Delta during 1700–1916, when they were strongly influenced by Athabasca River floodwaters. We compared results to metal concentrations in surficial bottom sediments sampled by RAMP (2010–2013) at downstream sites of the Athabasca River and distributaries. When normalized to lithium content, concentrations of vanadium (a metal of concern in the oil sands region) and other priority pollutants (Be, Cd, Cr, Cu, Pb, Ni, Zn) in nearly all of the RAMP river sediment samples lie below the upper 95% prediction interval linearly extrapolated from the river-derived lake sediments. Assuming the RAMP protocols obtained recently deposited sediment, this indicates that the metal concentrations in downstream Athabasca River sediment have not increased above pre-disturbance levels. Reference conditions derived from the lake sediment data were used to develop profiles of metal residual concentrations versus time for the RAMP river sediment data, which provides an excellent tool for decision-makers to identify and quantify levels of metal pollution for any given sample, and to monitor for future trends. We recommend that the approach be applied to resurrect the utility of RAMP data at other river sampling locations closer to the development, and for ongoing risk assessment. The approach is also readily transferable to other rivers where insufficient pre-disturbance reference data impairs an ability to determine if industrial activities are polluting downstream ecosystems.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".