Surface soil organic carbon losses in Dongting Lake floodplain as evidenced by field observations from 2013 to 2022
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Bibliographic record
Abstract
• The surface soil organic carbon stock of Dongting Lake in 2022 was 6.82 Tg C (2.87–13.48 Tg C). • Surface SOC was lost in Dongting Lake because of climatic and hydrological changes. • Above 21.43 m elevation, SOC loss accelerated with increasing elevation. • Raising the water level during drought periods may be an important way to enhance the carbon sequestration potential of wetlands. In floodplain wetlands, alterations in hydrological patterns resulting from climate change and human activities could potentially diminish the carbon sequestration capacity of the soils, thereby having a negative impact on global climate change. However, the magnitude of the influence of hydrological regime change on soil carbon remains inadequately monitored. To address this research gap, we collected 306 upper layer (0-20 cm) soil samples from the Dongting Lake floodplain between 2013 and 2022. The Random Forest (RF) algorithm was used to analyze the spatial distribution of soil organic carbon (SOC) in the upper soil layer of Dongting Lake floodplain and the impact of climate and hydrological changes in the past decade on surface SOC in the East Dongting Lake area was studied. In 2022, the SOC concentration of the Dongting Lake floodplain upper layer soil ranged from 3.34 to 17.67 g kg −1 , averaging 10.43 g kg −1 , with a corresponding SOC density of 2.65±0.49 kg m −2 and total SOC stock of 6.82 Tg C (2.87–13.48 Tg C). From 2013 to 2022, the SOC concentration of the upper soil layer of the East Dongting Lake area decreased from 18.37 g kg −1 to 10.82 g kg −1 . This reduction could be attributed to climate and hydrological changes which reduce SOC input by reducing vegetation growth and accelerating SOC decomposition. Above 21.4 m elevation, the amount of SOC loss increased with elevation, the loss being related to the decline in Miscanthus community biomass and greater susceptibility of higher altitude areas to climate and hydrological changes. Our results highlight the need for strengthening wetland SOC management to increase SOC in the soils to help combat climate change.
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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 | 0.001 |
| 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) | 0.001 | 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 it