Processes affecting greenhouse gas production in experimental boreal reservoirs
Bibliographic record
Abstract
Flooding land for water reservoir creation has many environmental impacts including the production of the greenhouse gases (GHG) carbon dioxide (CO2) and methane (CH4). To assess processes governing GHG emissions from the flooding of terrestrial carbon, three experimental reservoirs were constructed in upland boreal forest areas of differing carbon stores as part of the Flooded Upland Dynamics Experiment (FLUDEX). We calculated process‐based GHG budgets for these reservoirs over 5 years following the onset of flooding. Stable isotopic budgets of carbon were necessary to separate community respiration (CR), which produces CO2, from net primary production (NPP), which consumes CO2, and to separate CH4 production from CH4 consumption via oxidation. NPP removed up to 44% of the CO2 produced from CR. CR and NPP exhibited different year‐after‐year trends. CH4 flux to the atmosphere increased about twofold over 3 years, yet isotopic budgets showed CH4 production in flooded soils increased nearly tenfold. CH4 oxidation near the flooded soil‐water interface greatly decreased the CH4 flux from the water column to the atmosphere. Ebullition was the most important conduit of CH4 to the atmosphere after 3 years. Although CH4 production increased with time, the total GHG flux, in CO2 equivalents, declined. Contrary to expectations, neither CR nor total GHG fluxes were directly related to the quantity of organic carbon flooded. Instead, these reservoirs produced a strikingly similar amount of CO2 equivalents over 5 years.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".