Compression wood has a minor effect on the climate signal in tree-ring stable isotopes of montane Norway spruce
Bibliographic record
Abstract
Compression wood is a common tissue present in the trunk, branches and roots of mechanically stressed coniferous trees. Its main role is to increase the mechanical strength and regain the vertical orientation of a leaning stem. Compression wood is thought to influence the climate signal in different tree-ring measures. Hence trees containing compression wood are mostly excluded from tree-ring studies reconstructing past climate variability. There is a large gap of systematic work testing the potential effect of compression wood on the strength of the climate signal in different tree-ring parameters, and especially stable isotope records. Here we test for the first time the effect of compression wood contained in montane Norway spruce (Picea abies L. Karst) on both δ13C and δ18O tree-ring cellulose records by analyzing compression and opposite wood radii from several disturbed trees together with samples from undisturbed reference trees. We selected four trees tilted by geomorphic processes that were felled by wind, and four undisturbed reference trees in the Tatra Mountains, Poland. We qualitatively classified the strength of compression wood using wood cell anatomical characteristics (tracheid shape, cell wall thickness and presence of intercellular spaces). Then we developed tree-ring width, δ13C and δ18O chronologies from the compression wood radii and the opposite radii of the tilted trees, and from the radii of the reference trees. We tested the effect of compression wood on tree-ring cellulose δ13C and δ18O variability and on the climate signal strength. Only minor differences were found in the means of δ13C and δ18O compression, opposite and reference radii. The statistical relationships between climate variables, δ13C and δ18O remained consistent among all chronologies. Our findings suggest that moderately tilted trees containing compression wood can be used to both reconstruct past geomorphic activity, and stable-isotope based dendroclimatological research.
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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 | 0.000 | 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".