Reservoir Surfaces as Sources of Greenhouse Gases to the Atmosphere: A Global Estimate
Bibliographic record
Abstract
Following flooding of landscapes to create any kind of reservoir, terrestrial plants die and no longer assimilate carbon dioxide (CO2) by photosynthesis (Figure 1), resulting in the loss of a sink for atmospheric CO2. In addition, bacteria decompose the organic carbon that was stored in plants and soils, converting it to CO2 and methane (CH4), which are then released to the atmosphere. All of the reservoirs examined to date emit CO2 and CH4 to the atmosphere (Table 1), but different landscapes contain different amounts of stored organic carbon in soils and vegetation (Schlesinger 1997), and so the potential for gas production and loss varies from site to site. For example, in the boreal region of Canada, a worst-case scenario is flooded peatlands because they possess a large store of organic carbon held in peat, which can decompose and be returned to the atmosphere as greenhouse gases over a long period (Kelly et al. 1997). Reservoirs that flood peatlands probably emit more greenhouse gases in the long term than reservoirs created over upland boreal forests, which have thin soil layers and no peat deposits.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".