Soil factors controlling mineral N uptake by <i>Picea engelmannii</i> seedlings: the importance of gross NH<sub>4</sub><sup>+</sup> production rates
Bibliographic record
Abstract
* Hydroponic studies suggest that plant nitrogen (N) demand determines the rate of mineral N uptake; however, field observations show N limitation to be widespread. Field experiments are needed to understand soil factors controlling mineral N uptake. * We planted Picea engelmannii seedlings that had initially been grown from sterilized seeds, on a recently clearcut site. We applied a hybrid isotope dilution/pulse labelling technique to compare the gross production rate, concomitantly to the plant uptake rate, of soil mineral N. We also measured mineral N concentrations, microbial N, and percent ectomycorrhizal root tips. * Gross NH4+ production rate was the most important determinant of plant uptake rate. Exploratory path analysis suggested that plant uptake was also determined by microbial N, which was, in turn, determined by soil mineral N concentrations. Percent ectomycorrhizal root tips was negatively related to gross NO3- production rate and microbial N concentrations. * We conclude that nutrient flux density is important in controlling plant uptake. Mycorrhizal colonization may alter N dynamics in the rhizosphere without affecting mineral N uptake by seedlings.
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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".