The impact of atmospheric acid deposition on tree growth and forest understory vegetation in the Athabasca Oil Sands Region
Bibliographic record
Abstract
Atmospheric acid deposition is of major concern in the Athabasca Oil Sands Region (AOSR) in northern Alberta, Canada, which is home to the third largest oil reserve in the world. After decades of oil sands production in the AOSR, the potential impact of deposition on forest health, including tree growth and understory biodiversity, is still not clear. We evaluated the relationship of modelled/interpolate atmospheric deposition of nitrogen (N), sulphur (S), base cations (BC), and derived potential acid input (PAI) from surface oil sands mining with: (1) the radial growth (i.e. basal area increment; BAI) of jack pine (Pinus banksiana Lamb.) trees using data from two decadal time periods, prior to (1957-1966) and during (2001-2010) active oil sands development in the AOSR; and (2) forest understory vegetation (abundance, diversity, and composition), which is an important component of forest biodiversity. BAI of jack pine trees varied with N, S, and BC deposition between the two time periods, and with the direction of the site relative to main emission sources. Growth was higher in areas close to the oil sands surface mining operations prior to and after oil sands development. BAI was also positively related to atmospheric deposition in the recent period, but these relationships were weaker in the active period versus the non-active period. Understory vegetation - including vascular plant cover, richness, and diversity - increased in relation to modelled atmospheric N and S deposition. There was limited correlation between soil pH or the BC:Al ratio (indicators of soil acidification) and BAI and understory vegetation responses. No evidence was found for detrimental effects of atmospheric emissions (and subsequent deposition) from oil sands production on tree growth or forest understory vegetation. The results, if anything, suggest a fertilization effect due to enhanced atmospheric deposition of nitrogen compounds.
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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 | 0.001 | 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".