Changing sources and processes sustaining surface CO <sub>2</sub> and CH <sub>4</sub> fluxes along a tropical river to reservoir system
Bibliographic record
Abstract
Freshwaters are important emitters of carbon dioxide (CO 2 ) and methane (CH 4 ), two potent greenhouse gases (GHGs). While aquatic surface GHG fluxes have been extensively measured, there is much less information about their underlying sources. In lakes and reservoirs, surface GHG can originate from horizontal riverine flow, the hypolimnion, littoral sediments, and water column metabolism. These sources are generally studied separately, leading to a fragmented assessment of their relative role in sustaining CO 2 and CH 4 surface fluxes. In this study, we quantified sources and sinks of CO 2 and CH 4 in the epilimnion along a hydrological continuum in a permanently stratified tropical reservoir (Borneo). Results showed that horizontal inputs are an important source of both CO 2 and CH 4 (>90 % of surface emissions) in the upstream reservoir branches. However, this contribution fades along the hydrological continuum, becoming negligible in the main basin of the reservoir, where CO 2 and CH 4 are uncoupled and driven by different processes. In the main basin, vertical CO 2 inputs and sediment CH 4 inputs contributed to on average 60 % and 23 % respectively to the surface fluxes of the corresponding gas. Water column metabolism exhibited wide amplitude and range for both gases, making it a highly variable component, but with a large potential to influence surface GHG budgets in either direction. Overall our results show that sources sustaining surface CO 2 and CH 4 fluxes vary spatially and between the two gases, with internal metabolism acting as a fluctuating but key modulator. However, this study also highlights challenges and knowledge gaps related to estimating ecosystem-scale CO 2 and CH 4 metabolism, which hinder aquatic GHG flux predictions.
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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 | 0.000 |
| 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) | 0.001 | 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 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".