Regeneration responses influenced by single-tree selection harvesting in a mixed-species tree community in northern JapanThis article is one of a selection of papers published in the Special Forum IUFRO 1.05 Uneven-Aged Silvicultural Research Group Conference on Natural Disturbance-Based Silviculture: Managing for Complexity.
Bibliographic record
Abstract
The objective of this study was to assess the effects of fine-scale canopy disturbances induced by selection harvesting and its associated practices (artificial planting and machinery skidding) on the successful regeneration of tree species in a northern Japanese mixed forest. We set up 163 plots in a 6.7 ha permanent study stand where trees have been partially harvested at approximately 10-year intervals since 1974. The regeneration of trees (4324 stems·ha–1) occurred more frequently under closed canopies than under canopy gaps, except for a typical shade-intolerant species, Betula ermanii Cham. In particular, small canopy openings that tend to close quickly displayed higher understory tree regeneration densities likely due to the suppression of competition from dwarf bamboos. The surface soil disturbances that occurred during planting and harvesting even further enhanced understory regeneration. The results shown here should be generalized carefully because we have investigated only one stand. Nevertheless, our findings clearly indicated that the creation of small canopy gaps associated with site preparation that contains soil disturbances should be examined in management practices to maintain the community structure in this type of mixed forest.
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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 | 0.000 | 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".