Nutrient uptake dynamics across a gradient of nutrient concentrations and ratios at the landscape scale
Bibliographic record
Abstract
Abstract Understanding interactions between nutrient cycles is essential for recognizing and remediating human impacts on water quality, yet multielemental approaches to studying nutrient cycling in streams are currently rare. Here we utilized a relatively new approach (tracer additions for spiraling curve characterization) to examine uptake dynamics for three essential nutrients across a landscape that varied in absolute and relative nutrient availability. We measured nutrient uptake for soluble reactive phosphorous, ammonium‐nitrogen, and nitrate‐nitrogen in 16 headwater streams in the Catskill Mountains, New York. Across the landscape, ammonium‐nitrogen and soluble reactive phosphorus had shorter uptake lengths and higher uptake velocities than nitrate‐nitrogen. Ammonium‐nitrogen and soluble reactive phosphorus uptake velocities were tightly correlated, and the slope of the relationship did not differ from one, suggesting strong demand for both nutrients despite the high ambient water column dissolved inorganic nitrogen: soluble reactive phosphorus ratios. Ammonium‐nitrogen appeared to be the preferred form of nitrogen despite much higher nitrate‐nitrogen concentrations. The uptake rate of nitrate‐nitrogen was positively correlated with ambient soluble reactive phosphorus concentration and soluble reactive phosphorus areal uptake rate, suggesting that higher soluble reactive phosphorus concentrations alleviate phosphorus limitation and facilitate nitrate‐nitrogen uptake. In addition, these streams retained a large proportion of soluble reactive phosphorus, ammonium‐nitrogen, and nitrate‐nitrogen supplied by the watershed, demonstrating that these streams are important landscape filters for nutrients. Together, these results (1) indicated phosphorus limitation across the landscape but similarly high demand for ammonium‐nitrogen and (2) suggested that nitrate‐nitrogen uptake was influenced by variability in soluble reactive phosphorus availability and preference for ammonium‐nitrogen.
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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 | 0.001 | 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".