Above-ground biomass predicts growth limitation in amabilis fir and western hemlock seedlings
Bibliographic record
Abstract
Conifer regeneration on clearcut montane sites is frequently affected by post-planting growth stagnation. The ability to predict such stagnation would be a valuable asset to forest managers. In this study, we tested the usefulness of above-ground biomass and photosynthetic efficiency (as estimated by foliar nitrogen concentration) in diagnosing growth limitations in western hemlock (Tsuga heterophylla) and amabilis fir (Abies amabilis). Seedlings were grown under different silvicultural systems (clearcut, patch cut, green tree retention and shelterwood) and post-planting treatments (fertilization, vegetation removal) at the Montane Alternative Silvicultural Systems (MASS) site on Vancouver Island, BC. Foliar nitrogen was found to be a poor predictor of height and stem volume growth. However, above-ground biomass predicted current height and stem volume (year 3 after planting), as well as future stem volume (year 7 after planting), in both species. Above-ground biomass therefore represents a useful measure of likely future growth performance, and may provide early warning of incipient growth stagnation in these species. Key words: amabilis fir, Abies amabilis, biomass, western hemlock, Tsuga heterophylla, growth limitation, photosynthetic capacity, biomass, seedling growth, regeneration
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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) | 0.001 | 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".