Elevated temperature and nutrients lead to increased N2O emissions from salt marsh soils from cold and warm climates
Bibliographic record
Abstract
Abstract Salt marshes can attenuate nutrient pollution and store large amounts of ‘blue carbon’ in their soils, however, the value of sequestered carbon may be partially offset by nitrous oxide (N2O) emissions. Global climate and land use changes result in higher temperatures and inputs of reactive nitrogen (Nr) into coastal zones. Here, we investigated the combined effects of elevated temperature (ambient + 5℃) and Nr (double ambient concentrations) on nitrogen processing in marsh soils from two climatic regions (Quebec, Canada and Louisiana, U.S.) with two vegetation types, Sporobolus alterniflorus (= Spartina alterniflora) and Sporobolus pumilus (= Spartina patens), using 24-h laboratory incubation experiments. Potential N2O fluxes increased from minor sinks to major sources following elevated treatments across all four marsh sites. One day of potential N2O emissions under elevated treatments (representing either long-term sea surface warming or short-term ocean heatwaves effects on coastal marsh soil temperatures alongside pulses of N loading) offset 15–60% of the potential annual ambient N2O sink, depending on marsh site and vegetation type. Rates of potential denitrification were generally higher in high latitude than in low latitude marsh soils under ambient treatments, with low ratios of N2O:N2 indicating complete denitrification in high latitude marsh soils. Under elevated temperature and Nr treatments, potential denitrification was lower in high latitude soil but higher in low latitude soil as compared to ambient conditions, with incomplete denitrification observed except in Louisiana S. pumilus. Overall, our findings suggest that a combined increase in temperature and Nr has the potential to reduce salt marsh greenhouse gas (GHG) sinks under future global change scenarios.
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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".