Fine and coarse root parameters from mature black spruce displaying genetic × soil moisture interaction in growth
Bibliographic record
Abstract
Fine and coarse root biomass, C, and N mass parameters were assessed by root size and soil depths from soil cores in plots of 32-year-old black spruce ( Picea mariana (Mill.) Britton, Sterns & Poggenb.) from four full-sib families studied previously for drought tolerance and differential productivity on a dry and wet site. All fine and coarse root size categories had greater root biomass on the dry than on the wet site. Most of the site differences resided in 0–20 cm soil depth. The wet site had greater root N concentration than the dry site, despite the same soil N; thus, virtually no differences were observed in total fine and coarse root N mass between sites. Root N concentration declined with increases in both soil depth and root size. Fine roots (<2 mm) accounted for 73% and 38% of the total fine and coarse N and C mass, respectively. The dry site had lower needle mass and more fine root mass than the wet site, demonstrating an adaptation to moisture stress change through the rebalancing of resource-obtaining organs. Drought-tolerant families had the same quantity of fine roots as drought-intolerant families but were able to support more foliage and aboveground mass per unit fine root mass than intolerant families.
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 | 0.000 | 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".