Ecotoxicological effects of fluvial eroded bitumen sediments from the Alberta oil sands to model aquatic species
Bibliographic record
Abstract
To fully understand the ecological and cumulative effects of mining activities on the surrounding aquatic systems of the Canadian oil sands region, it is essential to understand the consequences of exposure to bitumen-containing soils/sediment from natural geomorphological processes. Both physical and chemical stress on aquatic biota can potentially result from exposure to natural bitumen, resulting from hillslope erosional processes and slumping of bankside soils into the rivers, affecting both riverbed habitat and water quality. The magnitude and duration of bitumen-containing soil's fluvial soils/erosional input into receiving watersheds depends on the interannual variability in the regional hydroclimatology and related seasonal and extreme flow events. The primary objective of this study was to evaluate the potential ecotoxicological effects associated with erosional input of riverbank bitumen soils using controlled exposures. A series of integrated, laboratory-based ecotoxicological bioassays were conducted using organisms with different ecological and functional traits (Daphnia magna (Cladocera), Physa acuta (Gastropoda), and Aliivibrio fischeri (Bacteria)). All model organisms were exposed to elutriates produced from natural bitumen from four different regional rivers: fresh bitumen from shoreline outcrops at the Steepbank River upper and lower reaches (STB-CF and STB-MF, respectively) and the lower-Ells River (EL-MF) and aged, fluvially processed/weathered bitumen from the shoreline of the Athabasca River (ATB-MF). All tested organisms responded negatively to STB-MF and EL-MF elutriates. Low toxicity was also observed in the STB-CF and ATB-MF samples. These results follow the chemical analysis of the parental material and elutriates, where higher levels of metals, polycyclic aromatic compounds and naphthenic acids were detected in the EL-MF sample. In summary, this study shows that eroded and transported bitumen-containing soils and sediments could be a natural source of contaminant exposure to aquatic biota. This fluvial pathway should be considered when assessing background toxicity and the toxicological and ecological effects of oil sands mining activities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".