Long-term effects of increment coring on Norway spruce mortality
Bibliographic record
Abstract
Increment coring of trees is a standard method in dendrochronology, wood anatomy, forest ecology, and forestry. However, increment coring is an invasive method that may result in tree decay and decreased physical stability of the cored tree. The long-term effects of coring on tree mortality are poorly understood for any tree species because long-term data sets are rare. We present results from a 40-year study on the effects of coring on tree mortality in a near-primary Norway spruce ( Picea abies (L.) Karst.) forest in the Swiss Alps (forest reserve Scatlè). In 1965–1966, 551 trees with a diameter at breast height ≥8 cm were cored within a 5.9 ha plot. Following a reassessment of the plot in 2006, we compared the mortality rates of the 551 trees cored in 1965 with those of similar trees from the uncored control group, i.e., trees that were similar in size (diameter at breast height), vitality, and forest layer class. Neither nonparametric tests nor logistic regression models indicate a significant influence of coring on tree mortality. Our results suggest that increment coring does not influence the mortality rate of P. abies within the study region. Additional studies in different environments and on different tree species are needed to evaluate the generality of our findings.
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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 | 0.002 |
| 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) | 0.001 | 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".