Landscape-scale regulators of water transparency in mountain lakes: implications of projected glacial loss
Bibliographic record
Abstract
We examined factors regulating water transparency in a set of 33 lakes located in the Canadian Rocky Mountains. Eighteen lakes had catchments that included glaciers and 15 did not. In each lake, we quantified midsummer attenuation rates for three ultraviolet wavelengths and photosynthetically active radiation and measured chromophoric dissolved organic matter (CDOM) absorbance, turbidity, and chlorophyll a fluorescence. We also used GIS to quantify characteristics of lake catchments. Across lakes, turbidity and CDOM absorbance were arrayed on orthogonal gradients that intersected in a region of low turbidity and low CDOM absorbance. Nonglacially fed lakes had low turbidity and attenuation rates were regulated by CDOM absorbance, which increased with the percentage of the catchment covered by vegetation. Glacially fed lakes had low CDOM absorbance and attenuation rates increased with turbidity, which increased with the percentage of the catchment covered by permanent ice. Glaciers are retreating rapidly in the Canadian Rockies. As catchments become deglaciated, turbidity will likely decrease and the regulator of lake transparency is likely to switch to CDOM, which will have broad implications for lake ecosystems.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".