Forest regeneration in northeastern Poland following a catastrophic blowdown
Bibliographic record
Abstract
The aims of the investigation were to (i) quantify the changes in natural regeneration and stand structure, (ii) determine the role of deadwood in the process of regeneration following the disturbance, and (iii) determine the effect of disturbance severity on tree recruitment. The study was conducted in the Szast Protected Forest, which was established after a blowdown in 2002. The results showed that the trees were mainly wind-snapped. The basal area of the slightly disturbed stands increased over time. Herb cover increased, whereas moss cover decreased in 2011. The disturbance severity influenced the density of tree species regeneration, moss and herb ground cover, species diversity, average tree height, tree vitality, and damage caused by herbivores. The density of natural regeneration increased and new species became established after the disturbance. Scots pine (Pinus sylvestris L.) was the dominant tree species during the regeneration process except in the severely disturbed stand from which wood had been removed; in this case, birch was the dominant species. Wind disturbance increased species diversity and created a new forest with a particular species structure and trees that varied in age and height. The results of this study will be useful for foresters and policymakers to change the existing approaches to large-scale disturbances in the Polish forests.
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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".