Investigating the spatial–temporal variation of nitrogen cycling in an urban river in the North China Plain
Bibliographic record
Abstract
Urban rivers are essential in retaining nutrients, but little is known about nitrogen cycling in these rivers in semiarid areas. We measured chemical and isotopic compositions of ammonium (NH4(+)-N) and nitrate (NO3(-)-N) to investigate spatial-temporal variation of nitrogen cycling in the Fuhe River in the North China Plain. Nitrogen pollution in the river was mainly induced by extra NH4(+)-N inputs which come from the discharges of urban sewage and effluents of wastewater treatment plants in upstream. NH4(+)-N obtained from decomposing organic matter of sediments can diffuse into the overlying water. Intense nitrification then occurs at the terrestrial-aquatic interface. Due to less vegetation in spring and autumn, loss of NH4(+)-N is mainly caused by nitrification. In contrast, significant NH4(+)-N is absorbed by plants in summer. NO3(-)-N generated from nitrification can be denitrified during the study period. The highest NO3(-)-N loss (about 86.3%) was observed in summer. The contribution of NO3(-)-N loss due to denitrification is 44.6%. The remaining 55.4% is due to plant uptake. The results suggested that nitrogen cycling in the river is related to temperature and dry-wet cycles. And vegetation restoration along the river could benefit the incremental improvements to the aquatic ecosystem.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".