FOG AND ACIDIFICATION IMPACTS ON ION BUDGETS OF BASINS IN NOVA SCOTIA, CANADA<sup>1</sup>
Bibliographic record
Abstract
ABSTRACT: We examined hydrogeochemical records for a dozen watersheds in and near Kejimkujik National Park in southwestern Nova Scotia by relating stream ion concentrations and fluxes to atmospheric deposition, stream type (lake inlet versus outlet; brown versus clear water), and watershed type (catchment area, topography, soils, and dominant forest cover type). We found that fog and dry deposition make important contributions to S, N, Cl, H, Ca, Mg, K, and Na inputs into these watersheds. Seasalt chloride deposition from rain, snow, fog, and dry deposition equal total stream outputs on a region‐wide basis. Chloride outputs, however, differ among watersheds by a factor of about two, likely due to local differences in air flow and vegetational fog interception. We found that most of the incoming N is absorbed by the vegetation, as stream water NO3‐ and NH4+ are very low. Our results also show that the vegetation and the soils absorb about half of the incoming SO42. In comparison with other North American watersheds with similar forest vegetation, Ca outputs are low, while Mg and K outputs are similar to other regions. Soil exchangeable Ca and soil cation exchange capacity are also very low. We found that first‐order forest streams with no upstream lakes have a distinct seasonal pattern that neither corresponds with the seasonal pattern of atmospheric deposition, nor with the seasonal pattern of downstream lake outlets.
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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 | 0.000 | 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".