Interspecific competition for nitrogen between early successional species and planted white spruce and jack pine seedlings
Bibliographic record
Abstract
Relatively little is known about belowground competition for nitrogen (N) between boreal forest species. The objective of this study was to compare the relative competitiveness of three early successional boreal forest species, trembling aspen (Populus tremuloides Michx.), fireweed (Epilobium angustifolium L.), and calamagrostis (Calamagrostis canadensis (Michx.) Beauv.), on 15N uptake and the growth response by containerized white spruce (Picea glauca (Moench) Voss) and jack pine (Pinus banksiana Lamb.) seedlings. Three densities (0, 2, and 6 plants/pot) of each competitor species were interplanted with individual seedlings in pots with 15N-labelled fertilizer and grown for 3 months. The conifer seedlings had the greatest fertilizer 15N uptake (129.5 and 82.3 µg/m2 root for white spruce and jack pine, respectively) when grown in monoculture and the lowest uptake when interplanted with six competitor plants (9.2 and 8.6 µg/m2 root for white spruce and jack pine, respectively). Whether grown in monoculture or with conifer seedlings, calamagrostis took up the greatest amount of fertilizer 15N. Vegetation management practices that reduce the establishment of this grass species in the field should benefit N uptake and growth of outplanted white spruce and jack pine 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) | 0.001 | 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".