Effect of Season and Machine Type on Performance of Semi- and Fully Mechanized Harvesting Systems in Beech-Dominated Stands
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Bibliographic record
Abstract
It is common to have large trees in mature hardwood-dominated stands. This is especially true for European beech (Fagussylvatica L.), which can also have a complex architecture. Such trees have predominantly been harvested using motor-manual operations. However, in an effort to increase occupational safety and allow for a more continuous wood flow to processing facilities, fully-mechanized systems are also being employed more frequently. This study was established to determine the effect of season (Fall or Winter) and harvester type (wheeled or tracked) on the performance of semi- and fully- mechanized harvesting systems deployed in beech-dominated stands. Time-and-motion analysis was conducted on a total of 927 trees located in two forest sites in Germany. The study indicated that new silvicultural prescriptions make it impossible to harvest all trees exclusively with mechanized systems, even in the case of the tracked harvester with its 14.5 m boom. Motor-manual intervention was needed with trees that were too large, malformed or out of reach. Motor-manual intervention was significantly more frequent for the wheeled (30%) than for the tracked harvester (18%). Once again, tree size had the strongest effect on time consumption in a linear model, which varied from 0.5 to over 6 min per tree. Season and machine effect were also significant but could only account for a small fraction of the total variability. For the same tree size, time consumption was higher with the wheeled harvester and during the fall. The model also indicated a significant relationship between tree form and time consumption, even though the explanatory contribution of this independent variable was relatively small, too. Good stem form resulted in a lower time consumption. The larger tracked harvester was generally more efficient, but also more expensive to own and operate: its higher costs must be weighed against the higher revenues. New silvicultural trends make it difficult to achieve full mechanization, but the results of this study may guide managers towards technical solutions that minimize motor-manual intervention to the advantage of higher productivity and better occupational safety.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it