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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".