Lake surface and downstream river temperature response to the retreat of a lake‐terminating glacier
Bibliographic record
Abstract
Abstract Glacier contributions to streamflow moderate summer water temperatures and help keep rivers cool during periods of hot, dry weather. As glaciers retreat, the length of channel exposed to solar radiation above a given point of interest would increase, which should ultimately result in higher water temperatures. However, formation of proglacial lakes may complicate river temperature response to glacier retreat. This study examined river and lake temperature response to the retreat of lake‐terminating Bridge Glacier, British Columbia, using a combination of manual spot and continuous river temperatures at a stream gauge, lake surface temperatures derived from Landsat imagery, and in situ lake temperatures made during a field campaign during summer 2013. Temperature data spanned the period from 1984 to 2022. Lake and river temperatures were relatively constant prior to and during a period of rapid retreat, but exhibited an upward trend following 2012, when iceberg density declined due to an apparent decrease in calving rate, resulting in an increase in lake surface area and river temperature of about 5°C even though the glacier remained lake terminating. In addition to providing the first longitudinal study of water temperature response to the retreat of a lake‐terminating glacier, this study adds to a body of literature that demonstrates that routine spot river temperatures, if collected in a consistent manner over a number of years, can provide valid information about river and stream temperature trends.
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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 | 0.000 | 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) | 0.001 | 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".