An assessment of nitrogen saturation in Pinus banksiana plots in the Athabasca Oil Sands Region, Alberta
Bibliographic record
Abstract
During the past 15 years, there has been a dramatic increase in the amount of reactive nitrogen (N) in the atmosphere, leading to concerns that chronic elevated N deposition may result in negative effects on natural ecosystems. This study examines the response of jack pine (Pinus banksiana) plots to N air concentrations within the Athabasca Oil Sands Region (AOSR) in northern Alberta, which has experienced elevated N emissions since the 1990s. Air concentrations of nitrogen dioxide (NO2), ammonia, and nitric acid at the study plots are generally low although NO2 is strongly correlated with sulphur dioxide indicating an exposure gradient associated with industrial emissions. Nitrogen concentrations in P. banksiana foliage and two lichen indicator species (Hypogymnia physodes and Evernia mesomorpha) were significantly correlated with annual NO2 exposure. Relationships between NO2 (or N exposure) and other aspects of N cycling were less evident. Nitrogen content and carbon to nitrogen ratio in the forest floor and soil or potential net N mineralization rates were not correlated with N exposure. Nitrification was negligible suggesting efficient ecosystem immobilization of current N deposition. Based on the response of foliage to N exposure, sites closest to industrial activity appear to be in the early stages of N saturation.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".