Night and day: short‐term variation in nitrogen chemistry and nitrous oxide emissions from streams
Bibliographic record
Abstract
Summary 1. Diel variation in metabolism contributes to variation in oxygen (O 2 ) concentrations in streams. This variation in O 2 and other parameters (e.g. pH) can in turn affect the rates of microbial nitrogen (N) processing, concentrations of nitrogenous solutes and production of the greenhouse gas nitrous oxide (N 2 O). We investigated diel variability in emissions of N 2 O and the magnitude of short‐term variability in N solutes across 10 streams. 2. Nitrous oxide fluxes varied on average 2.3‐fold over diel cycles. Concentrations would be underestimated by sampling around noon, but N 2 O fluxes would not show a consistent bias. Time‐weighted mean daily N 2 O flux was strongly related to nitrate concentration ( r 2 = 0.58). Diel patterns in N 2 O and dissolved N species were often complex (rather than simple sinusoidal curves), probably reflecting complex underlying processes. 3. Reliance on samples obtained around noon would overestimate daily mean nitrate concentrations by 5% and underestimate ammonium by 32% (average bias across all streams and dates). 4. Dissolved organic N did not show consistent day–night variation. However, the magnitude of diel variability was similar to that observed for dissolved inorganic N. Organic and inorganic N concentrations were often similar. Both appear to be dynamic components of stream N budgets. 5. The Intergovernmental Panel on Climate Change (IPCC) relies upon an emission factor to estimate indirect agricultural N 2 O emissions from streams and ground water. The measured emission factor (defined as the ratio of concentrations of N 2 O‐N to ‐N) was typically below the recently revised IPCC default figure. Measured values varied on average 1.8‐fold over approximately 24‐h periods and were slightly higher at night than by day. The emission factor was actually highest in streams that were net sinks for N 2 O, highlighting a conceptual problem in the current IPCC method. 6. Typical sampling programmes rely on daytime‐only sampling, which might cause bias in results. In our study streams, the bias was generally small. Diel variation in nitrate concentrations was related to mean temperature; variation in ammonium and N 2 O concentrations was greatest at low concentrations of nitrite and ammonium.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".