Assessing methane emissions and soil carbon stocks in the Camargue coastal wetlands: Management implications for climate change regulation
Bibliographic record
Abstract
Coastal wetlands are crucial in climate change regulation due to their capacity to act as either sinks or sources of carbon, resulting from the balance between greenhouse gas (GHG) emissions, mainly methane (CH4), and soil carbon sequestration. Despite the paramount role of wetlands in climate regulation few studies investigate both aspects. The Camargue is one of the largest wetlands in Europe, yet the ways in which environmental and anthropic factors drive carbon dynamics remain poorly studied. We examined GHG emissions and soil organic carbon (SOC) stocks and accumulation rates in twelve representative wetlands, including two rice fields, to gain insights into the carbon dynamics and how it is influenced by hydrology and salinity. Mean CH4 rates ranged between – 87.0 and 131.0 mg m−2 h−1and the main drivers were water conductivity and redox, water table depth and soil temperature. High emission rates were restricted to freshwater conditions during summer flooding periods whereas they were low in wetlands subjected to summer drought and water conductivity higher than 10 mS cm−1. Nitrous oxide emissions were low, ranging from – 0.5 to 0.9 mg N2O m−2 h−1. The SOC stocks in the upper meter ranged from 17 to 90 Mg OC ha−1. Our research highlights the critical role of low-saline wetlands in carbon budgeting which potentially are large sources of CH4 but also contain the largest SOC stocks in the Camargue. Natural hydroperiods, involving summer drought, can maintain them as carbon sinks, but altered hydrology can transform them into sources. Artificial freshwater supply during summer leads to substantial CH4 emissions, offsetting their SOC accumulation rates. In conclusion, we advocate for readjusting the altered hydrology in marshes and for the search of management compromises to ensure the compatibility of economic and leisure activities with the preservation of the inherent climate-regulating capacity of coastal wetlands.
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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 | 0.001 | 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 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".