Greenhouse gas dynamics in a freshwater wetland in southeastern Ontario: Field measurements and laboratory incubations
Bibliographic record
Abstract
AbstractConcentrations of dissolved carbon dioxide (CO₂), dissolved methane (CH₄), and dissolved nitrous oxide (N₂O) were measured in open water areas across a freshwater mineral wetland in the Ottawa valley. 268 samples were collected on 19 sampling days from September 16th, 2022 to February 5th, 2024. Average dissolved CO₂ ranged from 111 μmol/liter in the spring, to 2548 μmol/liter in mid-winter. Average dissolved CH₄ ranged from 3.33 μmol/liter in the autumn, to 1414 μmol/liter in mid-winter. Average dissolved N₂O concentrations ranged from 0.016 μmol/liter below ambient to 0.036 μmol/liter. CO₂, CH₄, and N₂O accumulated under ice, resulting in high concentrations in winter. Concentrations of CO₂ and CH₄ declined in the autumn and increased from the spring until the end of summer. In late summer, CO₂ and CH₄ concentrations were higher than during the mid-summer despite lower temperatures. These higher gas concentrations coincided with the presence of dense flocks of migrating Canada geese. To further investigate the potential influence of the Canada goose migration and other nutrient sources on greenhouse gas emissions, two laboratory incubations of saturated soils in sealed jars were performed. The first incubation compared a control group with treatment groups of K₂SO₄, KH₂PO₄, KNO₃, and biochar. Each group had five replicates measured 17 times over 141 days for concentrations of CO₂, CH₄, and N₂O. Additions of fertilizers and biochar did not have a large impact on measured gases. The second incubation compared a control group with treatment groups of two different application rates of goose feces and cattle manure. Each group had five replicates measured 20 times over 78 days for concentrations of CO₂, CH₄, and N₂O. Goose feces and cow manure additions led to an increase in peak production of CO₂, CH₄, and N₂O. This research demonstrates the importance of year-round sampling across an entire wetland system and a new understanding of seasonality that includes the influence of nutrient additions from migrating species and local land use
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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 | 0.002 | 0.001 |
| 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".