Net Ecosystem Carbon Balance of a Peat Bog Undergoing Restoration: Integrating CO<sub>2</sub> and CH<sub>4</sub> Fluxes From Eddy Covariance and Aquatic Evasion With DOC Drainage Fluxes
Bibliographic record
Abstract
Abstract Peatland ecosystems are generally carbon (C) sinks. However, the role of dissolved organic C (DOC) relative to gaseous fluxes of CO2 and CH4 in the C balance of these ecosystems has not often been studied. Dissolved C fluxes are important for understanding C partitioning within the peatland and the potential C drainage from it. This research was conducted in Burns Bog, a heavily impacted ecosystem near Vancouver, Canada, undergoing ecological restoration efforts by rewetting. Here we present data on (i) ecosystem‐scale fluxes of CO2 (net ecosystem exchange, NEE) and CH4 (FCH4) determined by eddy covariance, (ii) evasion fluxes of CO2 and CH4 from the water surface to estimate the role of open water in ecosystem‐scale fluxes, and (iii) DOC flux (fDOC) in water draining from the peatland. Our results showed that open water areas inside the footprint were a continual C source, emitting 47.0 ± 2.4 g C·m−2·year−1. DOC export (15.6 g C·m−2·year−1) was significant to the net ecosystem C balance, decreasing the magnitude of the eddy covariance‐determined C balance (i.e., NEE + FCH4) of −45.0 ± 16.8 g C·m−2·year−1 by 35%, resulting in a net ecosystem C balance (i.e., NEE + FCH4 + fDOC) of −29.7 ± 17.0 g C·m−2·year−1. Most of this offset occurred during the wetter nongrowing season when gross primary production was low and fDOC was relatively high.
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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".