Evaluating the biogeochemistry and microbial function in the Athabasca Oil Sands region: Understanding natural baselines for reclamation end-points
Bibliographic record
Abstract
Understanding the biogeochemical processes governed by the complex metabolic pathways of microbial communities is paramount in understanding overall ecosystem services. Their ability to adapt to the world’s harshest environments allows them to thrive in otherwise hostile environments. The Athabasca Oil Sands of Northern Alberta, Canada, constitutes one of the largest oil sands deposits in the world. This uniquely hydrocarbon-rich environment is a diverse and complex ecosystem governed by strong anthropogenic (i.e. industrial mine sites) and natural environmental gradients (i.e. substantial bitumen outcroppings). The economically significant oil sands deposit produces millions of barrels of bitumen daily, with waste materials (i.e. sands, clays, residual bitumen etc.) pumped into large settling basins called tailings ponds. The Government of Alberta requires oil sands operators to return their mine sites to a reclaimed landscape after mining has completed, thus leaving an enormous task of determining appropriate reclamation procedures, target end-points and water quality targets. However, what remains unknown is an understanding of the baseline biogeochemical fingerprint of the natural McMurray Formation (MF) – the geological strata constituting the mineable bitumen ore. Additionally, there has yet to be any studies focusing on the microbial function in the MF, a vital research gap that would provide insight into how the indigenous microbial communities deal with this ubiquitous, natural hydrocarbon presence. The research comprising the chapters of this dissertation, are the first to reveal the active, in-situ metabolism of the bacterial communities within the MF. Novel metatranscriptomics approaches from in-situ samples are used to characterize the microbial metabolic processes governing these ecosystems, to better understand what may constitute viable ecosystem reclamation end-points. Functional characterizations are compared to hydrocarbon signatures and redox state of the various study sites. Results indicate a unique microbial consortium with both energy and xenobiotic metabolic pathways tailored to the complex hydrocarbon substrate of the MF. Further, the sensitivity of this metatranscriptomics approach was tested and validated as a means of tracking hydrocarbon exposure down a river continuum. Clusters of closely related co-expressing genes revealed patterns of expression indicative of exposure to the hydrocarbons of the MF, providing interesting methodologies to track pollution exposure in a hydrodynamic context. Finally, a field-scale mesocosm study was used to track the biogeochemical evolution of tailings following a novel detoxification treatment and further compare back to the natural reference sites also studied. Treatments caused the reduction of toxic organics and the promotion of microbial taxa adept at metabolizing complex organics. These cumulative insights into the natural and anthropogenically impacted ecosystems of the Athabasca Oil Sands region provides much needed characterizations of reference/baseline environments from which to guide best management practices and gauge reclamation success.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".