Thinning around old oaks in spruce production forests: current practices show no positive effect on oak growth rates and need fine tuning
Bibliographic record
Abstract
The expansion of spruce-dominated forestry in Southern Sweden during the twentieth century has led to a considerable amount of oak (Quercus robur L.) woodlands being converted into stands dominated by planted spruce. The thinning of spruces around oak trees is currently done in Sweden to improve local diversity of insects, oak growing conditions and eventually decrease their mortality. To evaluate the effect of these treatments, we dendrochronologically studied growth of old (100–200 years old) oaks subjected to thinning of different intensity at nine locations in southern Sweden, and compared them to oaks located in nearby pastures. The overall pattern suggests that commonly adopted thinning intensities do not significantly affect oak growth. Oak growth was positively related to oak age and negatively to the amount of dead oak crown. Analyses of correlations between oak growth and summer drought conditions, as reflected by location-specific chronologies of the Monthly Drought Code (MDC), indicated that older trees exhibited generally negative correlations, whereas the correlation remained generally positive for the younger trees, both inside and outside forest stands. We propose that removal of spruces should be primarily done around older and healthier-looking trees.
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How this classification was reachedexpand
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 | 0.006 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".