Root biomass distribution under three cover types in a patchy Pseudotsuga menziesii forest in western Canada
Bibliographic record
Abstract
We investigated the relationship between cover type and root biomass distribution and allocation to different root size classes in a naturally regenerated, dry, Rocky Mountain Douglas-fir (Pseudotsuga menziesii var. glauca) forest in the southern interior of British Columbia, Canada. The site was selectively harvested 32 years previously; residual stems were 30 cm and 130–170 years old at breast height at the time of study. A total of nine pits (each measuring $1.0\ {\rm m}\times 1.0$ m) were excavated to a depth of 1.0 m under three different cover types: mature timber, grassy (Calamagrostis rubescens) openings (canopy gaps), and regeneration clumps. Total (all diameters) live root biomass ranged from 4.7 kg/m$^2$ under the mature timber to 1.9 kg/m$^2$ under both regeneration clumps and grassy openings. Thin root (0.1 cm < $\phi\leq 0.5$ cm) biomass was similar across all three cover types (0.8 kg/m$^2$). We suggest that the similarity of thin root biomass across the three cover types is indicative of strong root competition at this resource-poor site: there appears to be no below-ground "root gap" corresponding to the canopy opening above the pinegrass-dominated patches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".