Pesticides in Western Canadian Mountain Air and Soil
Bibliographic record
Abstract
The distribution of organochlorine pesticides (OCP; in past and current use) in the mountains of western Canada was determined by sampling air, soil, and lichen along three elevational transects in 2003-2004. Two transects west of the Continental Divide were located in Mount Revelstoke and Yoho National Park, while the Observation Peak transect in Banff National Park is east of the divide. XAD-based passive air samplers, yielding annually averaged air concentrations, were deployed, and soils were collected at all 22 sampling sites, whereas lichen were only sampled in Revelstoke. Back trajectory analysis showed limited air mass transport from the Prairies to the east, but a high frequency of air arriving from the southwest, which includes agricultural regions in British Columbia and Washington State. Endosulfan, dieldrin, and a-hexachlorocyclohexane were the most prevalent OCPs in air and soil; hexachlorobenzene was only abundant in air; chlorothalonil, dacthal, and pentachloronitrobenzene were also consistently present. OCP air concentrations were similar across the three transects, suggesting efficient atmospheric mixing on a local and regional scale. Soil concentrations and soil/air concentration ratios of many OCPs were significantly higher west of the Continental Divide. The soil and lichen concentrations of most OCPs increased with altitude in Revelstoke, and displayed maxima at intermediate elevations at Yoho and Observation Peak. These distribution patterns can be understood as being determined by the balance between atmospheric deposition to, and retention within, the soils. Higher deposition, due to more precipitation falling at lower temperatures, likely occurs west of the divide and at higher elevations. Higher retention, due to higher soil organic matter content, is believed to occur in soils below the tree line. Highest pesticide concentrations are thus found intemperate mountain soils that are rich in organic matter and receive large amounts of cold precipitation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".