Interactions in the uptake of amino acids, ammonium and nitrate ions in the Arctic salt‐marsh grass, <i> Puccinellia phryganodes</i>
Bibliographic record
Abstract
ABSTRACT The uptake of amino acids and inorganic nitrogen by roots of Puccinellia phryganodes was examined to assess the potential contribution of soluble organic nitrogen to plant nitrogen uptake in Arctic coastal marshes, where free amino acids constitute a substantial fraction of the soil‐soluble N pool. Short‐term excised root uptake experiments were performed using tillers grown hydroponically under controlled conditions in the field. The percentage reductions in ammonium uptake at moderate salinity (150 mm NaCl) compared with uptake at low salinity (50 mm NaCl) were double those of glycine, but glycine uptake was more adversely affected than ammonium uptake by low temperatures. Glycine uptake was higher at pH 5·7 than at pH 7·0 or 8·2. The glycine uptake was up‐regulated in response to glycine, whereas ammonium uptake was up‐regulated in response to ammonium starvation. Nitrate uptake was strongly down‐regulated when tillers were grown on either ammonium or glycine. In contrast to N‐starved roots, which absorbed ammonium ions more rapidly than glycine, the roots grown on glycine, ammonium and nitrate and not N‐starved prior to uptake absorbed glycine as rapidly as ammonium and nitrate ions combined. Overall, the results indicate that amino acids are probably an important source of nitrogen for P. phryganodes in Arctic coastal marshes.
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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".