Lake water chemistry and its relationship to shoreline residential development and natural landscape features in Algonquin Provincial Park, Ontario, Canada
Bibliographic record
Abstract
There is a scarcity of long-term chemical monitoring data for lakes in Algonquin Provincial Park (APP), with minimal understanding of the impacts of cottage-leases (e.g., cottage lots, campgrounds, and commercial leases) on lake water chemistry. We examine spatial patterns in water chemistry and landscape features of 32 reference and 22 cottage-lease lakes in APP. Multivariate techniques were used to examine differences in water chemistry, and to identify the subset of landscape features that best explain this variability. Breakpoint analysis was used to examine the relationship between gradients of water chemistry and specific landscape features. Lakes were separated along a primary gradient of ions and pH and a secondary gradient of nutrients and colour. These gradients were best explained by a combination of six landscape features (wetlands, elevation, lake depth, road length, and coniferous trees). Except for chloride, there was no statistically significant difference in water chemistry between cottage-lease and reference lakes. A roughly west-to-east gradient in catchment vegetation and lake chemistry was related to the location of the Algonquin Dome, a natural geological feature in APP, and the park’s glacial history. These results emphasize the importance of the park’s topography in influencing regional water chemistry.
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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 | 0.000 |
| 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".