Hydrogeochemistry Studies in the Oil Sands Region to Investigate the Role of Terrain Connectivity in Nitrogen Critical Loads
Bibliographic record
Abstract
Hydrology and geochemistry studies were conducted in the Athabasca Oil Sands region to better understand the water and nitrogen cycles at two selected sites in order to assess the potential for nitrogen transport between adjacent terrain units. A bog—poor fen—upland system was instrumented near Mariana Lakes (ML) (55.899° N, 112.090° W) and a rich fen—upland system was instrumented at JPH (57.122° N, 111.444° W), 100 km south and 45 km north of Fort McMurray, Alberta respectively. LiDAR surveys were initially conducted to delineate the watershed boundaries and topography and to select a range of specific locations for the installation of water table wells and groundwater piezometers. Field work, which included a range of physical measurements as well as water sampling for geochemical and isotopic characterization, was carried out mainly during the thaw seasons of 2011 to 2015. From analysis of the runoff response and nitrogen species abundances we estimate that nitrogen exchange between the wetlands and adjacent terrain units ranged between 2.2 and −3.1 kg/ha/year for rich fens, 0.6 to −1.1 kg/ha/year for poor fens, and between 0.6 and −2.5 kg/ha/year for bogs, predominantly via surface pathways and in the form of dissolved nitrate. A significant storage of dissolved ammonium (and also dissolved organic nitrogen) was found within the pore water of the bog-fen complex at Mariana Lakes, which we attribute to decomposition, although it is likely immobile under current hydrologic conditions, as suggested by tritium distributions. In comparison with the experimental loads of between 5 and 25 kg/ha/year, the potential nitrogen exchange with adjacent terrain units is expected to have only a minor or negligible influence, and is therefore of secondary importance for defining critical loads across the regional landscape. Climate change and development impacts may lead to significant mobilization of nitrogen storages, although more research is required to quantify the potential effects on local 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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".