Is bog water chemistry affected by increasing N and S deposition from oil sands development in Northern Alberta, Canada?
Bibliographic record
Abstract
Abstract Nitrogen and sulfur emissions from oil sands operations in northern Alberta, Canada have resulted in increasing deposition of N and S to the region’s ecosystems. To assess whether a changing N and S deposition regime affects bog porewater chemistry, we sampled bog porewater at sites at different distances from the oil sands industrial center from 2009 to 2012 (10-cm intervals to a depth of 1 m) and from 2009 to 2019 (top of the bog water table only). We hypothesized that: (1) as atmospheric N and S deposition increases with increasing proximity to the oil sands industrial center, surface porewater concentrations of NH4+, NO3−, DON, and SO42− would increase and (2) with increasing N and S deposition, elevated porewater concentrations of NH4+, NO3−, DON, and SO42− would be manifested increasingly deeper into the peat profile. We found weak evidence that oil sands N and S emissions affect bog porewater NH4+-N, NO3−-N, or DON concentrations. We found mixed evidence that increasing SO42− deposition results in increasing porewater SO42− concentrations. Current SO42− deposition, especially at bogs closest to the oil sands industrial center, likely exceeds the ability of the Sphagnum moss layer to retain S through net primary production, such that atmospherically deposited SO42− infiltrates downward into the peat column. Increasing porewater SO42− availability may stimulate dissimilatory sulfate reduction and/or inhibit CH4 production, potentially affecting carbon cycling and gaseous fluxes in these bogs.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".