Carbon accumulation and sequestration of lakes in China during the Holocene
Bibliographic record
Abstract
Understanding the responses of lake systems to past climate change and human activity is critical for assessing and predicting the fate of lake carbon (C) in the future. In this study, we synthesized records of the sediment accumulation from 82 lakes and of C sequestration from 58 lakes with direct organic C measurements throughout China. We also identified the controlling factors of the long-term sediment and C accumulation dynamics in these lakes during the past 12 ka (1 ka = 1000 cal yr BP). Our results indicated an overall increasing trend of sediment and C accumulation since 12 ka, with an accumulation peak in the last couple of millennia for lakes in China, corresponding to terrestrial organic matter input due to land-use change. The Holocene lake sediment accumulation rate (SAR) and C accumulation rate (CAR) averaged (mean ± SE) 0.47 ± 0.05 mm yr(-1) and 7.7 ± 1.4 g C m(-2) yr(-1) in China, respectively, comparable to the previous estimates for boreal and temperate regions. The SAR for lakes in the East Plain of subtropical China (1.05 ± 0.28 mm yr(-1) ) was higher than those in other regions (P < 0.05). However, CAR did not vary significantly among regions. Overall, the variability and history of climate and anthropogenic interference regulated the temporal and spatial dynamics of sediment and C sequestration for lakes in China. We estimated the total amount of C burial in lakes of China as 8.0 ± 1.0 Pg C. This first estimation of total C storage and dynamics in lakes of China confirms the importance of lakes in land C budget in monsoon-influenced regions.
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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".