Using diatoms to track road-salt seepage into small, shallow, softwater Ontario lakes
Bibliographic record
Abstract
Since the 1950s, the widespread application of road salt for winter road maintenance and safety in cold regions has led to increased conductivity levels in many freshwater systems. Salting practices have adversely affected freshwater biota; however, the magnitude of ecological impacts may vary by species and ecosystem. Here, we examine diatom assemblage changes during the past ∼200 years from the sedimentary records of five impacted lakes (measured specific conductance values of 149–350 µS·cm−1) and a reference lake (18 µS·cm−1) located in the Muskoka River Watershed, south-central Ontario, Canada. Diatom compositional changes in the road-salt-impacted sites were consistent with increasing conductivity and increased diatom-inferred (DI)-conductivity was evident during the latter half of the 20th century in the impacted lakes, concurrent with known road-salt application. The strongest predictor of DI-conductivity changes among the six lakes was the kilometre equivalents of roads within the watershed (i.e., kilometres of road × number of lanes). Similar to changes observed in a previous study focusing on cladoceran assemblages, we conclude that even modest applications of road salt can affect diatom assemblages in softwater lakes.
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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 | 0.001 | 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".