An Assessment of Traditional Chemical Indicators of Atmospheric Pollution in Northern Saskatchewan Forest Soils
Bibliographic record
Abstract
Core Ideas Concentrations of pollutants in Saskatchewan forest soils are low but are highly variable. Distinct spatial patterns in surface soil pollutant concentration are evident. Patterns in soil Hg and V and SO 4 2− are strongly related to soil organic matter. Concentrations of Cu, Ni and Zn influenced by soil factors in addition to organic matter. Atmospheric deposition plays a minor role in pollutant levels in northern Saskatchewan soils. Long‐range transport and subsequent atmospheric deposition of pollutants has led to soil contamination around the globe. Northern Saskatchewan is downwind of major emissions of sulfur (S), nitrogen (N), and heavy metals vanadium (V) and nickel (Ni) associated with oil sands activities, leading to concerns over possible soil contamination. In this study we sampled 200 forested sites spanning five ecoregions of Saskatchewan. Surface (A‐horizon) soils were measured for a suite of traditional chemical indicators of atmospheric pollution (e.g., SO 4 2– , NO 3 − , Hg, heavy metals). In general, metal concentrations in surface soils were among the lowest reported in the literature indicating low levels of soil contamination. Despite the remote location of the sites there was a large range in pollution soil indicators in surface soil. For example, Hg concentrations were between 0.6 and 53.3 μg g −1 , V concentrations varied from <0.02 to 161 mg kg −1 , and extractable SO 4 2– was between 0.2 and 52.2 mg kg −1 and distinct spatial patterns were evident. Higher concentrations of pollutants were observed in southern, eastern and northern parts of the study area. Much of the variability in surface soil chemistry was explained by soil factors and in particular organic matter as the dominant controls of these pollution indicators. Lower values of these indicators were found in sandy soils low in organic matter such as those occurring in the Athabasca Plain located south of Lake Athabasca closest to oil sands activities.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".