Changes in site productivity and the recovery of soil properties following wet- and dry-weather harvesting disturbances in the Atlantic Coastal Plain for a stand of age 10 years
Bibliographic record
Abstract
Wet-weather logging can cause severe soil physical disturbances and redistribute residues. Although some research indicates negative effects of such disturbances on individual tree growth, the long-term resilience and resistance of soils and the ameliorative effects of site preparation are not fully understood. Three 20 ha loblolly pine ( Pinus taeda L.) plantations located on fertile wet pine flats on the coastal plain of South Carolina were subjected to five treatment combinations of harvest (wet and dry) and site preparation. Mean tree heights were 10.2–11.5 m, and stand biomass ranged between 95 and 143 Mg/ha. A rank diagnostic indicates that wet-weather harvesting did not significantly change site productivity between rotations, and bedding improved site productivity. At the polypedon scale (0.04 ha), there were no significant differences in tree height, biomass, or the rank diagnostic among classes of soil physical disturbances or harvesting residues when bedding was employed. On nonbedded sites, some levels of disturbance appeared to be superior to minimally disturbed sites. Based on 10 year results, wet pine flats are apparently resistant and resilient to the effects of wet-weather harvesting.
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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 | 0.000 | 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".