Nutrient cycling in a poplar plantation (<i>Populus trichocarpa × Populus deltoides</i>'Beaupré') on former agricultural land in northern Belgium
Bibliographic record
Abstract
Hydrological fluxes, atmospheric deposition, litterfall, and soil percolation of the most important nutrients were measured in an 18-year-old poplar plantation on a well-drained silt loam soil during 2 consecutive years. Downward soil water flux and transpiration are the most important factors in the water balance. Around 80% of total nitrogen input (6.6 and 6.5 kmol·ha–1in years 1 and 2, respectively) originates from litterfall. After nitrification only a negligible amount of nitrate leaches during the growing season. Yearly uptake of nitrogen by the poplar ecosystem (woody biomass, leaves, and ground vegetation) approximately equals the input, of which more than 50% is accounted for by the leaves. This indicates very efficient nitrogen cycling. Total deposition of base cations originates from two processes, dry deposition (Mg2+and Ca2+) and canopy leaching (K+and Ca2+). Litter input of Ca2+represents about 83% of the total input (stand deposition + litterfall), Mg2+about 61%, and K+less then 50%. Percolation of base cations at 1 m depth is very limited. Rather high Ca2+and K+contents of the woody biomass can lead to high exports at harvest. Nutrient cycling in the poplar stand proved to be very efficient, with no significant nutrient losses.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".