Effects of nitrogen supply and wood species on <i>Tsuga canadensis</i> and <i>Betula alleghaniensis</i> seedling growth on decaying wood
Bibliographic record
Abstract
Eastern hemlock (Tsuga canadensis (L.) Carrière) and yellow birch (Betula alleghaniensis Britt.) in primary Michigan forests depend on decaying wood for seedling-establishment sites, but seedling densities vary across wood species (hemlock, yellow birch, and sugar maple (Acer saccharum Marsh.)). We collected seedlings and wood from a natural field experiment and conducted a companion greenhouse experiment to determine whether seedling mass and nitrogen (N) content varied with wood species and whether they were related to wood inorganic N supply. Yellow birch seedlings were largest on hemlock wood in the field (P = 0.003) and greenhouse (but P > 0.05), while hemlock seedling mass did not vary across wood species. N concentration and N mineralization rate varied by species (N concentration: hemlock < yellow birch < maple; N mineralization rate: hemlock > yellow birch ≈ maple), but neither seedling mass nor N content was significantly correlated with wood inorganic N supply. In the greenhouse, yellow birch seedlings responded to fertilization with N when growing on hemlock and maple but not yellow birch wood and appear to be limited by phosphorus when growing on yellow birch wood. We conclude that yellow birch seedling growth varies with wood species, and is limited by both N and phosphorus, while hemlock seedlings are unresponsive to variation in wood species during the first two growing seasons.
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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".