Salinization, warming, and loss of water clarity inhibit vertical mixing of small urban ponds
Bibliographic record
Abstract
Abstract Urbanization drives multiple environmental changes that influence critical ecosystem processes. Factors such as salinization by deicing road salts, reduced water clarity (and greater light attenuation) from eutrophication and sediment loading, and warming constrain not only the biodiversity of ponds, but also their physical mixing (with consequences for oxygen availability and the provision of ecosystem services). Leveraging an extensive urban gradient in the Greater Toronto Area, we collected summertime depth profiles from 50 stormwater retention ponds to investigate their vertical stratification. We found that water columns were generally stratified but contrary to expectations, we found relatively minor roles of basin area and depth. Instead, we discovered an overwhelming effect of salinity along with significant impacts of temperature and water clarity on water density gradients. Findings extend our fundamental understanding of mixing regimes in small, shallow waterbodies and indicate increasing risks to pond functioning in a warmer and saltier future.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".