The disturbance regime of Norway spruce forests in Bulgaria
Bibliographic record
Abstract
Natural disturbances are among the most important factors that shape forest dynamics and forest landscapes. However, the natural disturbance regime of Norway spruce (Picea abies (L.) Karst.) forests in Europe is not well understood. We studied the disturbance regimes in three forest reserves in Bulgaria (Parangalitsa, Bistrishko branishte, and Beglika), which are representative of the range of conditions typical for P. abies ecosystems in central and southern Europe. Our data indicated that large-scale disturbances were most numerous in forests that were between 120 and 160 years old, those with unimodal diameter at breast height (DBH) distributions, and especially those located in vulnerable topographic settings. Wind disturbances ranged up to 60 ha, followed in one case by a 200 ha Ips typographus (Linnaeus, 1758) outbreak. Older forests and those with more complex structures (i.e., reverse-J DBH) were characterized by numerous small gaps but were also affected by a few larger disturbances. In some old-growth forests at highly productive sites, gaps could be so numerous that the long-term existence of old trees may become an exception. Over the past centuries, the natural range of variability of these Norway spruce forests in Bulgaria appears to have been shaped mostly by wind and bark beetle disturbances of various sizes.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".