Carbon dioxide and methane exchange at a cool-temperate freshwater marsh
Bibliographic record
Abstract
Freshwater marshes have been shown to be strong sinks for carbon dioxide (CO 2 ) on an annual basis relative to other wetland types; however it is likely that these ecosystems are also strong emitters of methane (CH 4 ), reducing their carbon (C) sequestration potential. Multiyear C balances in these ecosystems are necessary therefore to determine their contribution to the global C cycle. Despite this, the number of multiyear studies in marshes is few, with, to the best of our knowledge, only one other Northern marsh C balance reported. This study presents five years of eddy covariance flux measurements of CO 2 , and four years of warm-season chamber measurements of CH 4 at a cool-temperate Typha angustifolia marsh. Annual average cumulative net ecosystem exchange of CO 2 (NEE) at the marsh was −224 ± 54 g C m −2 yr −1 (±SD) over the five-year period, ranging from −126 to −284 g C m −2 yr −1 . Enhancement of the ecosystem respiration during warmer spring, autumn and winter periods appeared the strongest determinant of annual NEE totals. Warm season fluxes of CH 4 from the Typha vegetation (avg. 1.0 ± 1.2 g C m −2 d −1 ) were significantly higher than fluxes from the water surface (0.5 ± 0.4 g C m −2 d −1 ) and unvegetated mats (0.2 ± 0.2 g C m −2 d −1 ). Air temperature was a primary driver of all CH 4 fluxes, while water table was not a significant correlate as water levels were always at or above the vegetative mat surfaces. Weighting by the surface cover proportion of water and vegetation yielded a net ecosystem CH 4 emission of 127 ± 19 g C m −2 yr −1 . Combining CO 2 and CH 4 , the annual C sink at the Mer Bleue marsh was reduced to −97 ± 57 g C m −2 yr −1 , illustrating the importance of accounting for CH 4 when generating marsh C budgets.
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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".