Methane and carbon dioxide evasion from a mosaic of Amazon lakes, river channels, and inundated forests
Bibliographic record
Abstract
Seasonally inundated forests are the largest type of wetland in the Amazon basin. Here we provide new data from inundated forests, a lake, and river channels during high water in the forested Anavilhanas archipelago (Negro River, Brazil). Evasion pathways of CH4 in flooded forests include tree trunks, diffusion from the water, and ebullition. Within flooded forest sites, diffusive CH4 fluxes were lowest (mean, 6.2 µmol m-2 h-1), ebullitive fluxes averaged 50 µmol m-2 h-1, and fluxes from the trees had the highest fluxes when expressed per inundated surface area (83 µmol m-2 h-1). The lake and river channels usually had higher CH4 and CO2 fluxes than inundated forests. Overall, mean CH4 fluxes from inundated forests in our study were lower than fluxes measured in nutrient-rich inundated forests. Our results contribute to understanding the heterogeneity of C fluxes from inundated forests. Water levels, currents and extent of inundated habitats contribute to variability in gas fluxes. Outgassing rates are expected to become more variable with projected periods of especially high and low water levels as the climate changes.
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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".