Nitrogen Accumulation by Conifer Seedlings and Competitor Species From <sup>15</sup> Nitrogen‐labeled Controlled‐Release Fertilizer
Bibliographic record
Abstract
A major impediment to the establishment of outplanted conifer seedlings is competition for available soil N by early successional species. The objective of this field study was to determine the fate of controlled‐release fertilizer (CRF) N in soils with outplanted white spruce ( Picea glauca [Moench] Voss.) and jack pine ( Pinus banksiana Lamb.) seedlings, and the effect of weed control or vegetation management (VM) on fertilizer N accumulation. Nitrogen‐15 labeled CRF was placed next to the seedling root plug during planting at four boreal mixed wood sites. After one growing season in the control plots, fertilizer N recovery as a percentage of 15 N added was 4% in seedlings, 3% in competing vegetation, <1% leached, and 85% residual CRF. After two growing seasons, fertilizer N recovery was 15% in seedlings, 20% in competing vegetation, <1% leached, and 58% residual CRF. Overall, VM increased seedling fertilizer N uptake by almost 300% compared with conifer seedlings in control plots. In VM plots, fertilizer bags contained more N than in control plots after two growing seasons. In both treatments, >50% of the fertilizer N remained in the fertilizer bag, presumably remaining available in subsequent seasons. Calamagrostis ( Calamagrostis canadensis ) was the primary competitor for fertilizer N in both growing seasons, with minor competition from fireweed ( Epilobium angustifolium L.), and aspen ( Populus tremuloides Michx.). The use of a point source CRF delivery method resulted in high fertilizer use efficiency (FUE), and minimized losses to competing vegetation and leaching.
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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".