Synoptic snapshots: monitoring lake water quality over 4 decades in an urbanizing region
Bibliographic record
Abstract
Doucet C, Johnston L, Hiscock A, Bermarija T, Hammond M, Holmes B, Smith T, Lalonde B, Parent D, Deacoff C, Scott R, Kurek J, Jamieson R. 2023. Synoptic snapshots: monitoring lake water quality over 4 decades in an urbanizing region. Lake Reserv Manage. XX: XX–XXX. Synoptic water quality surveys—measuring major ions, nutrients, pH, organic matter, and trace elements—have been conducted in ∼50 lakes in the Halifax Regional Municipality (Nova Scotia, Canada) once per decade since 1980. In this study, lake water quality over 40 yr was examined and urban development was evaluated as a possible driver of observed changes. More than half of the lakes experienced strong (>50%) increases in conductivity, iron, sodium, chloride, calcium, and total phosphorus (TP), and strong decreases in acidity (i.e., [H+]). Between 20% and 50% of the lakes experienced strong increases in nitrate, alkalinity, zinc, color, aluminum, dissolved organic carbon, and magnesium, and strong decreases in manganese and sulfate. In 2021, national guidelines for the protection of aquatic life were exceeded by chloride, aluminum, manganese, and arsenic in certain lakes. Land cover classification from circa 1980 and 2020 revealed that although change in urban development within the lake watersheds ranged from a decrease of 11 percentage points to an increase of 48 percentage points, the majority (90%) of watersheds experienced an increase. Urban development was associated with increased chloride, conductivity, sodium, calcium, and TP concentrations. Other parameters appear to be more influenced by hydrology, watershed characteristics, climate, and decreased acid deposition. Results highlight emerging water quality concerns, such as elevated aluminum concentrations, and increased concentrations of chloride, nutrients, and arsenic, which should be the focus of strategic monitoring and mitigation efforts.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".