Quantifying Carbon Dioxide and Methane Emissions and Carbon Dynamics from Flooded Boreal Forest Soil
Bibliographic record
Abstract
The boreal forest is subject to natural and anthropogenic disturbances, but the production of greenhouse gases as a result of flooding for hydroelectric power generation has received little attention. It was hypothesized that flooded soil would result in greater CO(2) and CH(4) emissions and carbon (C) fractionation compared with non-flooded soil. To evaluate this hypothesis, soil C and nitrogen (N) dynamics, CO(2) and CH(4) mean production rates, and (13)C fractionation in laboratory incubations at 14 and 21 degrees C under non-flooded and flooded conditions and its effect on labile and recalcitrant C sources were determined. A ferro-humic Podzol was collected at three different sites at the Experimental Lakes Area, Canada, with a high (19,834 g C m(-2)), medium (18,066 g C m(-2)), and low (11,060 g C m(-2)) soil organic C (SOC) stock. Soil organic C and total N stocks (g m(-2)) and concentrations (g kg(-1)) were significantly different (p < 0.05) among soil horizons within each of the three sites. Stable isotope analysis showed a significant enrichment in delta(13)C and delta(15)N with depth and an enrichment in delta(13)C and delta(15)N with decreasing SOC and N concentration. The mean CO(2) and CH(4) production rates were greatest in soil horizons with the highest SOC stock and were significantly higher at 21 degrees C and in flooded treatments. The delta(13)C of the evolved CO(2) (delta(13)C-CO(2)) became significantly enriched with time during decomposition, and the greatest degree of fractionation occurred in the organic Litter, Fungal, and Humic forest soil horizons and in soil with a high SOC stock compared with the mineral horizon and soil with a lower SOC stock. The delta(13)C-CO(2) was significantly depleted in flooded treatments compared with non-flooded treatments.
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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) | 0.000 | 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".