Spatial variation in nutrient dynamics among five different peatland types in the Alberta oil sands region
Bibliographic record
Abstract
Abstract Wetlands are found extensively throughout the Western Boreal Plain, a region under pressure because of disturbance by the oil and gas industries. To understand how wetland systems may respond to disturbance and set targets for reclamation efforts, it is necessary to understand natural variability in nutrient dynamics in the landscape. The purpose of this study was to characterize spatial variability in peatland nutrient (nitrogen, N, and phosphorus, P) dynamics in the Athabasca Oil Sands (AOS) region. N and P availability and net mineralization rates in the upper 10 cm layer of peat were examined during the peak growing season in five peatlands that fell along an apparent moisture gradient. N and P dynamics within and among the sites were related to water table position, peat moisture content and temperature. Phosphorus supply rates and total inorganic N pools and supply rates were generally elevated under wetter conditions, whereas nitrate (NO3−) pools and supply rates and P pools did not vary along a moisture gradient. In general, net immobilization was observed at the wetter sites where nutrient pools were elevated and net mineralization was observed at drier sites where nutrient pools were lower. Nutrient transformation rates were most strongly driven by warmer temperatures. Nutrient availability and immobilization rates were anomalously high at one peatland (a disturbed fen with a semi‐permanent road and decommissioned well pads). We suggest that reclamation and management practices should focus on regulating peatland hydrologic conditions, optimizing these for the most desirable nutrient levels for vegetation growth. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.000 | 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".