Long-term trends in catchment export and lake concentrations of base cations in the Dorset study area, central Ontario
Bibliographic record
Abstract
Decreases in exchangeable base cation reservoirs, base cation export, and lake concentrations have been reported for acid-sensitive regions in Europe and eastern North America. These decreases have produced smaller than anticipated increases in alkalinity in surface waters in response to reductions in sulphate emissions and may have ecological consequences. This study presents annual export rates of Ca, Mg, K, and Na from 20 forested catchments between 1978 and 1998 and concentrations in seven downstream lakes between 1975 and 2005 in an acid-sensitive region of central Ontario, Canada. In contrast to monovalent cation export, decreases in divalent cation export continued after an extended dry period ended. Lake concentration trends showed three distinct periods. The first period (1975–1976 to 1982–1983) coincided with high runoff and was characterized by relatively high Ca, Mg, and K concentrations. This was followed by a 10-year period of fluctuations around the long-term mean. Concentrations then dropped below the long-term means and remained 5%–20% below the means until 2004–2005. The latter trend in lake concentrations suggests that export likely remained low but stable after May 1998 (the last month for which export data are available). Na increased between 250% and 350% in Dickie and Harp lakes as a result of road salt contamination.
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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 | 0.001 |
| 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) | 0.001 | 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".