Divergent oxygen trends in ice-covered lakes driven by ice-cover decline and ecological memory
Bibliographic record
Abstract
Dissolved oxygen (DO) is an essential resource in ice-covered lakes, regulating water quality and biodiversity, including the survival of economically important fish species. Most of the world’s lakes seasonally freeze, often resulting in oxygen depletion as ice cover inhibits water column ventilation and snow cover limits photosynthesis while respiration continues. Widespread shortening of ice-cover duration in a warmer world might improve winter oxygenation, but this hypothesis remains untested. Here, we performed a systematic analysis of 6.6 million physical and chemical observations from 19,645 lakes in the Northern Hemisphere during 1960 to 2022. Contrary to expectations, under-ice DO trends ranged from significantly negative in small lakes (A surf <10 ha) (−0.14 ± 0.05 mg L −1 decade −1 ) to significantly positive in large lakes (≥10 4 ha) (0.11 ± 0.03 mg L −1 decade −1 ). This morphometric scaling emerged partly because ice-cover periods have shortened 2.2 times faster in large lakes compared to small lakes. Hierarchical modeling revealed that in smaller lakes, increasingly oxygen-depleted conditions in summer carried over to the ice-cover season, because fetch size limited wind-driven aeration in fall. As a result of this cross-seasonal ecological memory, under-ice hypoxic zones have expanded. Oxygen trended most negative in small eutrophic and humic lakes with high seasonal oxygen depletion rates. In larger lakes (≥10 3 ha), negligible summer deoxygenation, prolonged ventilation in fall, and shortening of the oxygen drawdown period in winter explained positive DO trends. However, in the vast majority of seasonally ice-covered lakes, which are small, continued climate warming is likely to exacerbate deoxygenation.
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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 | 0.000 | 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".