Vertical fine root distributions of western redcedar, western hemlock, and salal in old-growth cedarhemlock forests on northern Vancouver Island
Bibliographic record
Abstract
The vertical distributions of fine roots of western hemlock (Tsuga heterophylla (Raf.) Sarg.) western redcedar (Thuja plicata Donn ex D. Don), and salal (Gaultheria shallon Pursh) were characterized in old-growth cedarhemlock forests on northern Vancouver Island. Total biomasses of cedar, hemlock, and salal roots in the forest floor and upper mineral soil were 817, 620, and 187 g·m2, respectively. Hemlock and salal fine roots were concentrated in the upper forest floor, while cedar fine roots were evenly distributed through the profile. Salal and hemlock fine root densities (g·m3) in the forest floor and mineral soil were positively correlated, as were salal and cedar root biomass distributions (g·m2). Only salal and hemlock root densities were significantly correlated with N concentrations. Hemlock root densities were negatively correlated with total N, and salal root densities were negatively correlated with total N and soluble organic N. Based on fine root densities, hemlock and salal probably compete for resources in the upper forest floor, whereas cedar accesses resources in the lower organic and mineral soil horizons. The differences in the vertical distributions of cedar, hemlock, and salal fine roots may partly explain the co-occurrence and different productivities of the three species in cedar-hemlock forests.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".