Coarse woody debris in mid-aged stands: abandoned agricultural versus long-term forest land
Bibliographic record
Abstract
During the 20th century, large agricultural areas in Eastern Europe became forested after their abandonment. To explore the value of these new forests for biota, we assessed volumes of coarse woody debris (CWD) on random transects in mid-aged (4075 years old) stands. In mixed and deciduous forests that were not forested in the 1930s, downed tree (log) volumes were about two times lower than in cutover sites. The effect on snag volume depended on site type and was generally nonsignificant. Large-diameter CWD showed similar proportions in the long-term and new forest areas, but large, well-decayed trunks tended to be less frequent in the latter. No reduction of dead wood volume was found in new pine stands, 98% of which had previously been classified as mires (bogs). Hence the origin of mid-aged successional forests had affected their CWD supply (particularly logs) to some extent, but the general scarcity of CWD all over the forest land indicated much larger (at least five-fold) losses due to timber harvesting. We conclude that naturally reforested areas should not be automatically excluded from reserve establishment or other CWD-related conservation programmes.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".