The effect of interspecific competition on conifer seedling growth and nitrogen availability measured using ion-exchange membranes
Bibliographic record
Abstract
During the early establishment phase, outplanted white spruce (Picea glauca (Moench) Voss) and jack pine (Pinus banksiana Lamb.) seedlings are vulnerable to lethargic growth or mortality because of interspecific competition for soil nutrients, particularly N. Accurately quantifying the degree of N competition is essential for supporting effective vegetation management (VM) decisions. This study evaluated the use of in situ burials of ion-exchange membrane (IEM; Plant Root SimulatorTM-probes) for quantifying differences in soil N supply rate between different VM treatments and the relationship of this N availability index to early growth of conifer seedlings at four boreal forest sites. At most sites, the effect of noncrop N uptake on soil N availability was apparent, with smaller NH4+-N, NO3-N, and total dissolved inorganic N (DIN) supply rates in control plots than in VM plots. Total DIN supply rate was correlated (R2 = 0.60 to 0.73, P < 0.01) with seedling height, root-collar diameter, and stem volume growth. Ammonium-N supply rate was better correlated than NO3-N supply rate with conifer seedling growth, which is in agreement with preferential NH4+-N uptake by conifer species. The results of this study support the use of in situ burials of IEM for measuring soil N availability during the early establishment phase.
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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 | 0.001 |
| 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".