The effect of tree dimension on the diversity of bark microhabitat structures and bark use in Douglas-fir (<i>Pseudotsuga menziesii</i> var. <i>menziesii</i>)
Bibliographic record
Abstract
The focus of this study was to investigate the role of tree dimension and associated bark structures for high structural complexity and high natural biodiversity in forest ecosystems. Two-hundred and ninety-one Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirbel) Franco) trees in two regions of the US Pacific Northwest were investigated for the relationship between tree diameter and bark thickness (measured as bark fissure depth) and the relationships of both to bark microhabitats and signs of bark use. Our results emphasize the habitat function of tree bark of large-diameter Douglas-fir trees. Many bark microhabitat types and their total abundance significantly increased with increasing tree diameter and bark thickness. These were bark pockets with and without decaying substrate, bowls in the bark, and signs of bark use, e.g., small holes from woodpecker drillings and large insects, large bark excavations from woodpeckers, spider funnel webs, natural cavities at the stem base without decay, and the occurrence of herb vegetation at the tree base. In forest monitoring, tree diameter may be a good indicator of the number of bark microhabitats and of bark thickness because it is strongly related to both of these variables. However, because of the high variability of bark thickness in large-diameter trees, we suggest monitoring bark fissure depth if an ecological evaluation of Douglas-fir forests is needed.
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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 | 0.001 |
| 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".