Vertical distribution and radial growth of coarse roots in pure and mixed stands of <i>Fagus sylvatica</i> and <i>Picea abies</i>
Bibliographic record
Abstract
The vertical distribution of roots greater than 2 mm diameter was determined from digital images covering 116-m2 profile walls in soil pits in pure stands of European beech (Fagus sylvatica L.) and of Norway spruce (Picea abies (L.) Karst.) and in a mixed stand of both species. Radial root growth was assessed for roots greater than 5 mm diameter by growth ring analysis. Beech roots showed maximum density at the 10- to 20-cm depth, whereas the density of spruce roots decreased exponentially with increasing soil depth. Roots of both species reached the maximum excavation depth (1 m) in their monospecific stands. However, the root system of spruce was shallower in the mixture with beech, where large roots (diameter (d) >20 mm) were limited to the upper 10 cm. Beech roots reached the same rooting depth as in the pure stand but showed higher root densities in deeper soil layers. Neither root diameter nor root growth of any species was correlated with soil depth. Radial root growth of beech exceeded that of spruce significantly in both pure and mixed stands. Radial growth rate of beech roots further increased when mixed with spruce. The enhancement of beech root growth in the mixed stand suggests a higher belowground competitive ability of beech compared with spruce; as a result the spruce root system developed even shallower in the mixed versus in the pure stand.
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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 | 0.000 |
| 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) | 0.000 | 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".