Regional assessments of lake shrinkage in response to permafrost thaw and climate change across arctic north American basins: regulating effects of lake geometry
Bibliographic record
Abstract
Changes in Arctic lake extent are critical indicators of regional water balance and permafrost stability. While previous studies have documented widespread lake shrinkage or disappearance under warming and permafrost thaw, it remains unclear whether lake geometric features- such as shoreline length, area, shape complexity, and depth- modulate the lake response to these drivers. This study examined lake area dynamics for more than 4000 lakes across the Yukon and Mackenzie basins using Landsat-derived annual lake area products from 2000 to 2020. We employed boosted regression trees to quantify the contributions of climate change and permafrost thaw to the observed trends and to evaluate the regulatory effect of lake geometric features. Our results revealed that while some lakes expanded, the average trend for individual lakes was characterized by reductions, with the mean rates of −0.20 ha/yr and −0.14 ha/yr in the Mackenzie and Yukon basins, respectively. The shrinkage of lake area mainly driven by climate change and permafrost thaw was regulated by the geometric features of lakes, with lakes having longer shorelines or larger areas demonstrating more pronounced responses to permafrost thaw. These findings emphasize the regulatory effect of lake geometric features on the response of lake area changes to climate change and permafrost thaw, indicating the need to consider lake geometric features when predicting lake evolution in the context of Arctic permafrost thaw.
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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 | 0.001 |
| 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".