Assessing tree-related microhabitat retention according to a harvest gradient using tree-defect surveys as proxies in Eastern Canadian mixedwood forests
Bibliographic record
Abstract
Tree-related microhabitats (hereafter “TreMs”) play a key role in forest biodiversity. However, harvesting may cause their erosion. In North America, knowledge about TreMs is still lacking but defect surveys are largely available in managed forests. The objectives of our study were: (1) to demonstrate that defect surveys can be a reliable resource to identify TreMs; and, (2)to evaluate the capacity of silvicultural treatments to maintain TreM abundance and diversity according to a harvest gradient.To achieve these objectives, we identified TreMs from a defect survey performed the year a harvest gradient was applied to20 plots, including uncut control, shelterwood treatments removing 50%, 43% and 36% of basal area, and clearcut (4 plots/treatment). The density and composition of TreMs were then compared based on treatments. Overall, 38% of defectsactually corresponded to TreMs, confirming that tree-defects can be used as TreM proxies. Bark loss was the most abundantTreM. While there was practically no TreM in clearcuts, all shelterwood treatments initially maintained TreM diversity anddensity at the same values found in uncut control plots. Shelterwood systems, especially those maintaining a continuouscover, could therefore prove helpful to sustain TreMs and their biodiversity in managed forests.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 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".