Evaluating nitrate uptake in a Rocky Mountain stream using labelled <sup>15</sup>N and ambient nitrate chemistry
Bibliographic record
Abstract
Abstract Background aqueous chemistry and 15Nnitrate tracer injection methods were used to calculate in‐stream nitrate uptake metrics at Red Canyon Creek, a third‐order stream in the Rocky Mountains in the state of Wyoming, United States. ‘Net’ nitrate uptake lengths, which reflect both nitrate uptake and regeneration, and ‘gross’ nitrate uptake lengths, which exclude re‐mineralization, were quantified separately from background nitrate chemistry and 15N labelling tracer data, respectively. Gross nitrate uptake lengths, from tracer injections of 15N labelled nitrate, ranged from 502 to 3140 m. Net nitrate uptake lengths, from background nitrate chemistry downstream of a point source, ranged from 1170 to 4330 m. Diurnal changes in uptake lengths suggest the importance of nitrate utilization by autotrophs in the stream and benthic zone. The differences between net and gross nitrate uptake lengths along lower reaches of Red Canyon Creek allowed us to estimate the nitrate regeneration rate, which was 0·056–0·080 µmol m−2 s−1 during the day and 0·0062–0·0083 µmol m−2 s−1 at night. Spatial patterns of streambed pore water chemistry indicate those areas of the hyporheic zone where denitrification was likely occurring. Permanent log dams generated stronger redox gradients in the hyporheic zone than areas with transient beaver dams. By combining isotopically labelled nitrate additions, estimates of uptake from background aqueous nitrate chemistry and characterization of redox conditions in the hyporheic zone, we were able to determine the nitrate regeneration rate and the redox processes responsible for nitrogen cycling in the hyporheic zone. Copyright © 2010 John Wiley & Sons, Ltd.
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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) | 0.000 | 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 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".