The Role of Climate and Lake Size in Regulating the Ice Phenology of Boreal Lakes
Bibliographic record
Abstract
Abstract We quantified the relationships between seasonal air temperatures and ice phenology for a 0.54 km 2 boreal lake in Northwestern Ontario, Canada using a 50‐year time series (1970–2019). Significant temporal trends in the duration of ice cover (−4.0 days decade −1 ) occurred over the study period and both ice‐on and ice‐off dates were highly predictable from seasonal air temperatures. While temporal trends in ice‐off dates were not significant, ice‐on dates trended later by 2.2 days decade −1 , and both ice‐off dates and the duration of ice‐cover became increasingly variable over the study period. For three consecutive winter seasons, we also evaluated regional variations of ice‐phenology and snow and ice‐thickness from 9 to 30 boreal lakes across a lake size gradient (0.02–26 km 2 ) using ground based and satellite observations. Regional variation of ice‐on dates (30–45 days), ice‐off dates (10–21 days), and total duration of ice‐cover (22–38 days) between lakes displayed significant nonlinear relationships to lake size across all years. Regional variation of ice‐off dates was structured according to lake size, and appeared driven by relationships between lake size, snow thickness, and ice thickness. Multiple linear regression and generalized additive modeling approaches to predict ice‐on and ice‐off dates at the regional scale by integrating the effects of air temperature and lake size had similar performance, explaining >90% of the variance of observed.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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".