The response of greenhouse gas fluxes and nutrient filtration potential to increases in temperature and nutrient loading from salt marsh soils across a climatic gradient
Bibliographic record
Abstract
Salt marshes sequester large amounts of “blue carbon” helping to mitigate climate change. This negative climate feedback, however, may be partially offset by increases in emissions of the potent greenhouse gases (GHGs) CH4 and N2O from marsh soils, which some studies have shown to vary with temperature, nutrient availability and vegetation zones. Additionally, these ecosystems may have the capacity to remove reactive nitrogen potentially reducing nutrient pollution in coastal zones. Salt marshes of the northern Northwest Atlantic are typically vegetated by Spartina alterniflora at the lowermost elevations and Spartina patens at higher elevations. On the Mississippi Delta, in the northern Gulf of Mexico, Spartina alterniflora is typically found in the most saline marshes, whereas Spartina patens is found at slightly lower salinities. We evaluated the response of GHG production and denitrification to elevated temperature and nutrients through laboratory incubations of intact soil cores. Cores were collected from Spartina patens and Spartina alterniflora zones in the St. Lawrence River estuary, Quebec and in the Barataria-Terrebonne Basin, Louisiana, areas with distinctly different climates. We used 15N-NO3- and 15N-NH4+ tracers to partition the sources of N2O produced by denitrification and nitrification, respectively, as well as total N2 production by denitrification using the 15N-GAS Flux method. We also measured potential fluxes of CH4, N2O and CO2. Incubation experiments were performed under ambient conditions and with elevated temperature and nutrient conditions. Different environmental conditions between vegetation zones and climatic regions are expected to result in different fluxes of CH4 and N2O, and rates of denitrification. Elevated temperature and nutrients are expected to increase GHG fluxes, however, it is unclear how net N2 production, as a remedy for nitrate attenuation in marshes, will respond. Our aim is to increase our understanding of the impact of increased temperature and nitrogen loading on nitrogen removal capacity and the GHG climate feedback in different vegetation zones of salt marshes of two climatic regions.
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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) | 0.001 | 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".