Long-term thinning effects on the forest floor and the foliar nutrient status of Norway spruce stands in the Belgian Ardennes
Bibliographic record
Abstract
The long-term impact (30 years) of three contrasting thinning programs (unthinned, moderately thinned, and heavily thinned) on selected forest-floor properties and on the foliar nutrient status of Norway spruce (Picea abies (L.) Karst.) stands (46, 50, and 67 years old) was evaluated at three sites on acid soils in the Belgian Ardennes. Sampling involved needles (current-year, 1-year-old, and recently fallen) and soil organic layers (OL, OF, OH, OA). For all samples, dry mass and element concentrations (C, N, P, Ca, Mg, K, Na, Mn, Al, Fe) were determined. Linear mixed models were used to analyze these data and showed that forest-floor mass was negatively affected by thinning (p = 0.0003) and that the N concentration in the forest floor increased with thinning intensity (p = 0.0008), while its Mn concentration decreased (p < 0.0001). The N, P, and K concentrations in the current-year needles were decreased by thinning (p < 0.05), while the Ca, Mg, and Na concentrations were not affected. We hypothesize that thinning negatively affected N, P, and K nutrition by removing the nutrients contained in the thinned trees and by decreasing the forest-floor thickness, thus reducing its nutrient contents and its ability to support root growth.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".