Differential sources and controls of soil CO2 efflux in a sugar maple forest
Bibliographic record
Abstract
This study determined controls on snow free season soil CO2 efflux in a sugar maple forest in central Ontario. Soil CO2 efflux data were collected with soil temperature, moisture, nutrient pools and sorption capacity. Soil CO2 efflux ranged from 0.2 to 30 pmol/m2/s. Temperature and moisture explained 49% of the variance (p<0.0001), with carbon pools and sorption capacity explaining an additional 31% (p<0.0001). The forest floor carbon pool was negatively correlated with soil CO2 efflux, indicating it is a net carbon sink to the atmosphere. In contrast, a positive correlation was found between soil CO2 efflux and the carbon-rich Ah horizon, indicating Ah carbon is actively respired, and the carbon-poor Ae horizon with high sorption capacity, indicating Ae serves as a trap for dissolved carbon flowing downslope that is subsequently respired. This finding has implications for managing forests for carbon offsets, because the majority of carbon is respired from older soils underneath the forest floor.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".