Response of Douglas-fir seedlings to a brief pulse of 15N-labeled nutrients
Bibliographic record
Abstract
The temporal distribution of soil nutrients is heterogeneous, and thus the uptake, storage and later remobilization of brief nutrient pulses may be critical for growth in nutrient-limited habitats. We investigated the response of 2-year-old Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) seedlings receiving a low nutrient supply to a 15-day nutrient pulse (containing 250 ppm nitrogen (N) as 10 atom % 15NH4 15NO3). The nutrient pulse was imposed in late July, toward the end of the seedlings' third growing season, and subsequent changes in dry mass and N content over the following 3 months were determined from destructive harvests. We tested three hypotheses: (1) N from the nutrient pulse is rapidly assimilated and accumulated primarily in needles and roots; (2) this accumulated N is later remobilized to support new growth; and (3) the nutrient pulse leads to a larger second flush of shoot growth. Seedlings increased their N content by 175 mg (67%) in response to the nutrient pulse. Nitrogen was taken up preferentially into younger tissues, especially the secondary flush and current-year roots. Immediately after the nutrient pulse, tissue N concentrations were high and supported subsequent increases in dry mass. Over 3 months, seedlings receiving the nutrient pulse added twice as much dry mass as control seedlings, and even after 3 months of growth, N concentrations remained greater than in controls. Current-year and older needles were the only components whose dry mass did not increase over this period. The nutrient pulse increased the size of the second flush, but it was still a minor component of increments in dry mass (approximately 10% of the total dry mass increment) and N content (23%). The relatively modest increases in N content during autumn could be accounted for by soil uptake and there was no evidence that N was remobilized to support growth of new tissues. Short-term (15 days) elevated N uptake led to sustained growth in the long term (> 3 months), and thus growth rate was to a large extent decoupled from current nutrient supply.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".