Years of extraction determines CO <sub>2</sub> and CH <sub>4</sub> emissions from an actively extracted peatland in eastern Québec, Canada
Bibliographic record
Abstract
Abstract. Draining and extracting peat alters a peatland’s control of CO2 and CH4 emissions. Carbon (C) emissions from peatlands undergoing extraction are not well constrained due to a lack of measurements. We determine the effect that production duration (years of extraction) has on the CO2 and CH4 emissions from an actively extracted peatland over three years of measurements (2018–2020). We studied five sectors identified by the year when extraction began (1987, 2007, 2010, 2013, 2016). Higher average CO2 and CH4 emissions were measured from the drainage ditches (CO2: 2.05 ± 0.12 g C m-2 d-1; CH4: 72.0 ± 18.0 mg C m-2 d-1) compared to the field surface (CO2: 0.9 ± 0.06 g C m-2 d-1; CH4: 9.2 ± 4.0 mg C m-2 d-1 regardless of sector. For peat fields, CO2 fluxes were highest in the youngest sector, which opened in 2016 (1.5 ± 0.2 g C m-2 d-1). The four older sectors all had similar mean CO2 fluxes (~0.65 g C m-2 d-1) that were statistically different from the mean 2016 CO2 flux. A spatial effect on CO2 fluxes was observed solely within the 2016 sector, where CO2 emissions were highest from the centre of the peat field and declined towards the drainage ditches. These observations occur due to operators' surface contouring to facilitate drainage. The domed shape and subsequent peat removal resulted in a difference in surface peat age hence different humification and lability. 14C dating confirmed that the remaining peat contained within the 2016 sector was younger than peat within the 2007 sector and that peat age is younger toward the centre of the field in both sectors. Humification indices derived from mid-infrared spectrometry (MIRS) (1630/1090 cm-1) indicated that peat humification increases with increasing years of extraction. Laboratory incubation experiments showed that CO2 production potentials of surface peat samples from the 2016 sector increased toward the centre of the field and were higher than for samples taken from the 1987 and 2007 sectors. Our results indicate that peatlands under extraction are a net source of C where emissions are high in the first few years after opening a field for extraction and then decline to about half the initial value and remain at this level for several decades, and the ditches remain a 2 to 3 times greater source than the fields, but represent < 7 % of the total area of a field.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".