Agricultural Land Use Impacts Aquatic Greenhouse Gas Emissions From Wetlands in the Canadian Prairie Pothole Region
Bibliographic record
Abstract
Abstract The Prairie Pothole Region (PPR) is the largest wetland complex in North America, with millions of wetlands punctuating the landscapes of Canada and the United States. Here, wetlands have been dramatically impacted by agricultural land use, with unclear implications for regional to global greenhouse gas (GHG) emissions budgets. By surveying wetlands across all three Canadian prairie provinces in the PPR, we show that emissions patterns of carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) from aquatic habitats differ among wetlands embedded in cropland versus perennial landcover. Wetlands in cropped landscapes had double the aquatic diffusive emissions (17.8 ± 29.3 vs. 7.7 ± 13.9 g CO 2 ‐ eq m −2 d −1 ) largely driven by CH 4 . Structural equation modeling showed that all three GHGs responded differently to the surrounding landscape properties. Emissions of CH 4 were the most sensitive to land use, responding positively to the elevated phosphorus content and lower sulfate content in cropped settings, despite higher organic matter content in wetlands in perennial landscapes. Aquatic N 2 O emissions were negligible, while CO 2 emissions were high, but not strongly related to agricultural land use. While our estimates of aquatic CH 4 emissions from PPR wetlands were high (15.6 ± 37.2 mmol CH 4 m −2 d −1 ), accounting for fluxes from vegetated and soil habitats would lead to whole‐wetland emissions rates that are lower and comparable to wetlands in other biomes. Our study represents an important step toward understanding wetland emission responses to land use in the PPR and other wetland‐rich agricultural landscapes.
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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 | 0.000 | 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 teacher head, 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".