Hot tops, cold bottoms: Synergistic climate warming and shielding effects increase carbon burial in lakes
Bibliographic record
Abstract
Abstract In this article, we challenge the notion that global warming stimulates organic matter mineralization and increases greenhouse gas emissions in lakes via direct temperature effects. We show that the interactive effects of warming and transparency loss due to eutrophication or browning overrides atmospheric warming alone. Thermal shielding enables a longer and more stable stratification that results in bottom‐water cooling, prolonged anoxia, and enhanced carbon preservation in a large proportion of global lakes. These effects are strongest in shallow lakes where an additional burial of 4.5 Tg C yr −1 increases current global estimates by 9%. Despite more burial, the net global warming potential of lakes will increase via enhanced methane production, related to prolonged periods of anoxia, rather than warming. Our understanding of how whole‐lake carbon cycling responds to climate change needs revision, as the synergistic influence of warming and transparency loss has much broader ecosystem level functional consequences.
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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 | 0.000 |
| 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) | 0.000 | 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".